Evaluation and integration of functional annotation pipelines for newly sequenced organisms: the potato genome as a test case.

PubMed

Amar, David; Frades, Itziar; Danek, Agnieszka; Goldberg, Tatyana; Sharma, Sanjeev K; Hedley, Pete E; Proux-Wera, Estelle; Andreasson, Erik; Shamir, Ron; Tzfadia, Oren; Alexandersson, Erik

2014-12-05

For most organisms, even if their genome sequence is available, little functional information about individual genes or proteins exists. Several annotation pipelines have been developed for functional analysis based on sequence, 'omics', and literature data. However, researchers encounter little guidance on how well they perform. Here, we used the recently sequenced potato genome as a case study. The potato genome was selected since its genome is newly sequenced and it is a non-model plant even if there is relatively ample information on individual potato genes, and multiple gene expression profiles are available. We show that the automatic gene annotations of potato have low accuracy when compared to a "gold standard" based on experimentally validated potato genes. Furthermore, we evaluate six state-of-the-art annotation pipelines and show that their predictions are markedly dissimilar (Jaccard similarity coefficient of 0.27 between pipelines on average). To overcome this discrepancy, we introduce a simple GO structure-based algorithm that reconciles the predictions of the different pipelines. We show that the integrated annotation covers more genes, increases by over 50% the number of highly co-expressed GO processes, and obtains much higher agreement with the gold standard. We find that different annotation pipelines produce different results, and show how to integrate them into a unified annotation that is of higher quality than each single pipeline. We offer an improved functional annotation of both PGSC and ITAG potato gene models, as well as tools that can be applied to additional pipelines and improve annotation in other organisms. This will greatly aid future functional analysis of '-omics' datasets from potato and other organisms with newly sequenced genomes. The new potato annotations are available with this paper.

A domain-centric solution to functional genomics via dcGO Predictor

PubMed Central

2013-01-01

Background Computational/manual annotations of protein functions are one of the first routes to making sense of a newly sequenced genome. Protein domain predictions form an essential part of this annotation process. This is due to the natural modularity of proteins with domains as structural, evolutionary and functional units. Sometimes two, three, or more adjacent domains (called supra-domains) are the operational unit responsible for a function, e.g. via a binding site at the interface. These supra-domains have contributed to functional diversification in higher organisms. Traditionally functional ontologies have been applied to individual proteins, rather than families of related domains and supra-domains. We expect, however, to some extent functional signals can be carried by protein domains and supra-domains, and consequently used in function prediction and functional genomics. Results Here we present a domain-centric Gene Ontology (dcGO) perspective. We generalize a framework for automatically inferring ontological terms associated with domains and supra-domains from full-length sequence annotations. This general framework has been applied specifically to primary protein-level annotations from UniProtKB-GOA, generating GO term associations with SCOP domains and supra-domains. The resulting 'dcGO Predictor', can be used to provide functional annotation to protein sequences. The functional annotation of sequences in the Critical Assessment of Function Annotation (CAFA) has been used as a valuable opportunity to validate our method and to be assessed by the community. The functional annotation of all completely sequenced genomes has demonstrated the potential for domain-centric GO enrichment analysis to yield functional insights into newly sequenced or yet-to-be-annotated genomes. This generalized framework we have presented has also been applied to other domain classifications such as InterPro and Pfam, and other ontologies such as mammalian phenotype and disease ontology. The dcGO and its predictor are available at http://supfam.org/SUPERFAMILY/dcGO including an enrichment analysis tool. Conclusions As functional units, domains offer a unique perspective on function prediction regardless of whether proteins are multi-domain or single-domain. The 'dcGO Predictor' holds great promise for contributing to a domain-centric functional understanding of genomes in the next generation sequencing era. PMID:23514627

MIPS bacterial genomes functional annotation benchmark dataset.

PubMed

Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

2005-05-15

Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

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

IMG ER: a system for microbial genome annotation expert review and curation.

PubMed

Markowitz, Victor M; Mavromatis, Konstantinos; Ivanova, Natalia N; Chen, I-Min A; Chu, Ken; Kyrpides, Nikos C

2009-09-01

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.

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

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.

AgBase: supporting functional modeling in agricultural organisms

PubMed Central

McCarthy, Fiona M.; Gresham, Cathy R.; Buza, Teresia J.; Chouvarine, Philippe; Pillai, Lakshmi R.; Kumar, Ranjit; Ozkan, Seval; Wang, Hui; Manda, Prashanti; Arick, Tony; Bridges, Susan M.; Burgess, Shane C.

2011-01-01

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website. PMID:21075795

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

PubMed

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

Discovery and Characterization of Chromatin States for Systematic Annotation of the Human Genome

NASA Astrophysics Data System (ADS)

Ernst, Jason; Kellis, Manolis

A plethora of epigenetic modifications have been described in the human genome and shown to play diverse roles in gene regulation, cellular differentiation and the onset of disease. Although individual modifications have been linked to the activity levels of various genetic functional elements, their combinatorial patterns are still unresolved and their potential for systematic de novo genome annotation remains untapped. Here, we use a multivariate Hidden Markov Model to reveal chromatin states in human T cells, based on recurrent and spatially coherent combinations of chromatin marks.We define 51 distinct chromatin states, including promoter-associated, transcription-associated, active intergenic, largescale repressed and repeat-associated states. Each chromatin state shows specific enrichments in functional annotations, sequence motifs and specific experimentally observed characteristics, suggesting distinct biological roles. This approach provides a complementary functional annotation of the human genome that reveals the genome-wide locations of diverse classes of epigenetic function.

AGORA : Organellar genome annotation from the amino acid and nucleotide references.

PubMed

Jung, Jaehee; Kim, Jong Im; Jeong, Young-Sik; Yi, Gangman

2018-03-29

Next-generation sequencing (NGS) technologies have led to the accumulation of highthroughput sequence data from various organisms in biology. To apply gene annotation of organellar genomes for various organisms, more optimized tools for functional gene annotation are required. Almost all gene annotation tools are mainly focused on the chloroplast genome of land plants or the mitochondrial genome of animals.We have developed a web application AGORA for the fast, user-friendly, and improved annotations of organellar genomes. AGORA annotates genes based on a BLAST-based homology search and clustering with selected reference sequences from the NCBI database or user-defined uploaded data. AGORA can annotate the functional genes in almost all mitochondrion and plastid genomes of eukaryotes. The gene annotation of a genome with an exon-intron structure within a gene or inverted repeat region is also available. It provides information of start and end positions of each gene, BLAST results compared with the reference sequence, and visualization of gene map by OGDRAW. Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/gene_project/AGORA/.The main module of the tool is implemented by the python and php, and the web page is built by the HTML and CSS to support all browsers. gangman@dongguk.edu.

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

PubMed

Klimke, William; O'Donovan, Claire; White, Owen; Brister, J Rodney; Clark, Karen; Fedorov, Boris; Mizrachi, Ilene; Pruitt, Kim D; Tatusova, Tatiana

2011-10-15

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.

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

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

USDA-ARS?s Scientific Manuscript database

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...

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

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_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism. PMID:26196387

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_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism.

FIGENIX: Intelligent automation of genomic annotation: expertise integration in a new software platform

PubMed Central

Gouret, Philippe; Vitiello, Vérane; Balandraud, Nathalie; Gilles, André; Pontarotti, Pierre; Danchin, Etienne GJ

2005-01-01

Background Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps. Results Here we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset). The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data. Conclusion The core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest. PMID:16083500

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes

PubMed Central

Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-01

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. PMID:27899624

Expanded microbial genome coverage and improved protein family annotation in the COG database

PubMed Central

Galperin, Michael Y.; Makarova, Kira S.; Wolf, Yuri I.; Koonin, Eugene V.

2015-01-01

Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the COGs is expected to become an important tool for microbial genomics. PMID:25428365

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

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).

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Elo; Huang, Amy; Cadag, Eithon

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

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

Gene Ontology annotation of the rice blast fungus, Magnaporthe oryzae

PubMed Central

Meng, Shaowu; Brown, Douglas E; Ebbole, Daniel J; Torto-Alalibo, Trudy; Oh, Yeon Yee; Deng, Jixin; Mitchell, Thomas K; Dean, Ralph A

2009-01-01

Background Magnaporthe oryzae, the causal agent of blast disease of rice, is the most destructive disease of rice worldwide. The genome of this fungal pathogen has been sequenced and an automated annotation has recently been updated to Version 6 . However, a comprehensive manual curation remains to be performed. Gene Ontology (GO) annotation is a valuable means of assigning functional information using standardized vocabulary. We report an overview of the GO annotation for Version 5 of M. oryzae genome assembly. Methods A similarity-based (i.e., computational) GO annotation with manual review was conducted, which was then integrated with a literature-based GO annotation with computational assistance. For similarity-based GO annotation a stringent reciprocal best hits method was used to identify similarity between predicted proteins of M. oryzae and GO proteins from multiple organisms with published associations to GO terms. Significant alignment pairs were manually reviewed. Functional assignments were further cross-validated with manually reviewed data, conserved domains, or data determined by wet lab experiments. Additionally, biological appropriateness of the functional assignments was manually checked. Results In total, 6,286 proteins received GO term assignment via the homology-based annotation, including 2,870 hypothetical proteins. Literature-based experimental evidence, such as microarray, MPSS, T-DNA insertion mutation, or gene knockout mutation, resulted in 2,810 proteins being annotated with GO terms. Of these, 1,673 proteins were annotated with new terms developed for Plant-Associated Microbe Gene Ontology (PAMGO). In addition, 67 experiment-determined secreted proteins were annotated with PAMGO terms. Integration of the two data sets resulted in 7,412 proteins (57%) being annotated with 1,957 distinct and specific GO terms. Unannotated proteins were assigned to the 3 root terms. The Version 5 GO annotation is publically queryable via the GO site . Additionally, the genome of M. oryzae is constantly being refined and updated as new information is incorporated. For the latest GO annotation of Version 6 genome, please visit our website . The preliminary GO annotation of Version 6 genome is placed at a local MySql database that is publically queryable via a user-friendly interface Adhoc Query System. Conclusion Our analysis provides comprehensive and robust GO annotations of the M. oryzae genome assemblies that will be solid foundations for further functional interrogation of M. oryzae. PMID:19278556

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.

MEGANTE: A Web-Based System for Integrated Plant Genome Annotation

PubMed Central

Numa, Hisataka; Itoh, Takeshi

2014-01-01

The recent advancement of high-throughput genome sequencing technologies has resulted in a considerable increase in demands for large-scale genome annotation. While annotation is a crucial step for downstream data analyses and experimental studies, this process requires substantial expertise and knowledge of bioinformatics. Here we present MEGANTE, a web-based annotation system that makes plant genome annotation easy for researchers unfamiliar with bioinformatics. Without any complicated configuration, users can perform genomic sequence annotations simply by uploading a sequence and selecting the species to query. MEGANTE automatically runs several analysis programs and integrates the results to select the appropriate consensus exon–intron structures and to predict open reading frames (ORFs) at each locus. Functional annotation, including a similarity search against known proteins and a functional domain search, are also performed for the predicted ORFs. The resultant annotation information is visualized with a widely used genome browser, GBrowse. For ease of analysis, the results can be downloaded in Microsoft Excel format. All of the query sequences and annotation results are stored on the server side so that users can access their own data from virtually anywhere on the web. The current release of MEGANTE targets 24 plant species from the Brassicaceae, Fabaceae, Musaceae, Poaceae, Salicaceae, Solanaceae, Rosaceae and Vitaceae families, and it allows users to submit a sequence up to 10 Mb in length and to save up to 100 sequences with the annotation information on the server. The MEGANTE web service is available at https://megante.dna.affrc.go.jp/. PMID:24253915

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes.

PubMed

Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-04

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A draft annotation and overview of the human genome

PubMed Central

Wright, Fred A; Lemon, William J; Zhao, Wei D; Sears, Russell; Zhuo, Degen; Wang, Jian-Ping; Yang, Hee-Yung; Baer, Troy; Stredney, Don; Spitzner, Joe; Stutz, Al; Krahe, Ralf; Yuan, Bo

2001-01-01

Background The recent draft assembly of the human genome provides a unified basis for describing genomic structure and function. The draft is sufficiently accurate to provide useful annotation, enabling direct observations of previously inferred biological phenomena. Results We report here a functionally annotated human gene index placed directly on the genome. The index is based on the integration of public transcript, protein, and mapping information, supplemented with computational prediction. We describe numerous global features of the genome and examine the relationship of various genetic maps with the assembly. In addition, initial sequence analysis reveals highly ordered chromosomal landscapes associated with paralogous gene clusters and distinct functional compartments. Finally, these annotation data were synthesized to produce observations of gene density and number that accord well with historical estimates. Such a global approach had previously been described only for chromosomes 21 and 22, which together account for 2.2% of the genome. Conclusions We estimate that the genome contains 65,000-75,000 transcriptional units, with exon sequences comprising 4%. The creation of a comprehensive gene index requires the synthesis of all available computational and experimental evidence. PMID:11516338

Microbial genome analysis: the COG approach.

PubMed

Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2017-09-14

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Mutant phenotypes for thousands of bacterial genes of unknown function

DOE PAGES

Price, Morgan N.; Wetmore, Kelly M.; Waters, R. Jordan; ...

2018-05-16

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because theymore » are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Lastly, our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.« less

Mutant phenotypes for thousands of bacterial genes of unknown function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, Morgan N.; Wetmore, Kelly M.; Waters, R. Jordan

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because theymore » are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Lastly, our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.« less

Maize - GO annotation methods, evaluation, and review (Maize-GAMER)

USDA-ARS?s Scientific Manuscript database

Making a genome sequence accessible and useful involves three basic steps: genome assembly, structural annotation, and functional annotation. The quality of data generated at each step influences the accuracy of inferences that can be made, with high-quality analyses produce better datasets resultin...

Ten steps to get started in Genome Assembly and Annotation

PubMed Central

Dominguez Del Angel, Victoria; Hjerde, Erik; Sterck, Lieven; Capella-Gutierrez, Salvadors; Notredame, Cederic; Vinnere Pettersson, Olga; Amselem, Joelle; Bouri, Laurent; Bocs, Stephanie; Klopp, Christophe; Gibrat, Jean-Francois; Vlasova, Anna; Leskosek, Brane L.; Soler, Lucile; Binzer-Panchal, Mahesh; Lantz, Henrik

2018-01-01

As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation. The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project. Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA. Different sequencing technologies and generally applicable workflows for genome assembly are also detailed. We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows. The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR). PMID:29568489

Expanded microbial genome coverage and improved protein family annotation in the COG database.

PubMed

Galperin, Michael Y; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2015-01-01

Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the COGs is expected to become an important tool for microbial genomics. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by US Government employees and is in the public domain in the US.

Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

PubMed Central

Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim; Krogsgaard, Steen; Nielsen, Jens

2008-01-01

Background Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number of hypothetical proteins accounted for more than 50% of the annotated genes. Considering the industrial importance of this fungus, it is therefore valuable to improve the annotation and further integrate genomic information with biochemical and physiological information available for this microorganism and other related fungi. Here we proposed the gene prediction by construction of an A. oryzae Expressed Sequence Tag (EST) library, sequencing and assembly. We enhanced the function assignment by our developed annotation strategy. The resulting better annotation was used to reconstruct the metabolic network leading to a genome scale metabolic model of A. oryzae. Results Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted in assignment of new putative functions to 1,469 hypothetical proteins already present in the A. oryzae genome database. Using the substantially improved annotated genome we reconstructed the metabolic network of A. oryzae. This network contains 729 enzymes, 1,314 enzyme-encoding genes, 1,073 metabolites and 1,846 (1,053 unique) biochemical reactions. The metabolic reactions are compartmentalized into the cytosol, the mitochondria, the peroxisome and the extracellular space. Transport steps between the compartments and the extracellular space represent 281 reactions, of which 161 are unique. The metabolic model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion A much enhanced annotation of the A. oryzae genome was performed and a genome-scale metabolic model of A. oryzae was reconstructed. The model accurately predicted the growth and biomass yield on different carbon sources. The model serves as an important resource for gaining further insight into our understanding of A. oryzae physiology. PMID:18500999

INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

PubMed Central

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B.

2013-01-01

Background The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. Results We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. Conclusions We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo. PMID:24324765

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

PubMed

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba Alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B

2013-01-01

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.

GFam: a platform for automatic annotation of gene families.

PubMed

Sasidharan, Rajkumar; Nepusz, Tamás; Swarbreck, David; Huala, Eva; Paccanaro, Alberto

2012-10-01

We have developed GFam, a platform for automatic annotation of gene/protein families. GFam provides a framework for genome initiatives and model organism resources to build domain-based families, derive meaningful functional labels and offers a seamless approach to propagate functional annotation across periodic genome updates. GFam is a hybrid approach that uses a greedy algorithm to chain component domains from InterPro annotation provided by its 12 member resources followed by a sequence-based connected component analysis of un-annotated sequence regions to derive consensus domain architecture for each sequence and subsequently generate families based on common architectures. Our integrated approach increases sequence coverage by 7.2 percentage points and residue coverage by 14.6 percentage points higher than the coverage relative to the best single-constituent database within InterPro for the proteome of Arabidopsis. The true power of GFam lies in maximizing annotation provided by the different InterPro data sources that offer resource-specific coverage for different regions of a sequence. GFam's capability to capture higher sequence and residue coverage can be useful for genome annotation, comparative genomics and functional studies. GFam is a general-purpose software and can be used for any collection of protein sequences. The software is open source and can be obtained from http://www.paccanarolab.org/software/gfam/.

MaizeGDB, the maize model organism database

USDA-ARS?s Scientific Manuscript database

MaizeGDB is the maize research community's database for maize genetic and genomic information. In this seminar I will outline our current endeavors including a full website redesign, the status of maize genome assembly and annotation projects, and work toward genome functional annotation. Mechanis...

Community annotation and bioinformatics workforce development in concert--Little Skate Genome Annotation Workshops and Jamborees.

PubMed

Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.

Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees

PubMed Central

Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832

GenomeRNAi: a database for cell-based RNAi phenotypes.

PubMed

Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

2007-01-01

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at http://rnai.dkfz.de.

GenomeRNAi: a database for cell-based RNAi phenotypes

PubMed Central

Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

2007-01-01

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at PMID:17135194

Social networks to biological networks: systems biology of Mycobacterium tuberculosis.

PubMed

Vashisht, Rohit; Bhardwaj, Anshu; Osdd Consortium; Brahmachari, Samir K

2013-07-01

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

MicroScope: a platform for microbial genome annotation and comparative genomics

PubMed Central

Vallenet, D.; Engelen, S.; Mornico, D.; Cruveiller, S.; Fleury, L.; Lajus, A.; Rouy, Z.; Roche, D.; Salvignol, G.; Scarpelli, C.; Médigue, C.

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope’s rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone. Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc PMID:20157493

MicroScope: a platform for microbial genome annotation and comparative genomics.

PubMed

Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

PubMed Central

Pham, Phillip H.; Shipman, William J.; Erikson, Galina A.; Schork, Nicholas J.; Torkamani, Ali

2015-01-01

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease – without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER. PMID:25706643

BG7: A New Approach for Bacterial Genome Annotation Designed for Next Generation Sequencing Data

PubMed Central

Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Pareja, Eduardo; Tobes, Raquel

2012-01-01

BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version – which is developed in Java, takes advantage of Amazon Web Services (AWS) cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future. PMID:23185310

A Resource of Quantitative Functional Annotation for Homo sapiens Genes.

PubMed

Taşan, Murat; Drabkin, Harold J; Beaver, John E; Chua, Hon Nian; Dunham, Julie; Tian, Weidong; Blake, Judith A; Roth, Frederick P

2012-02-01

The body of human genomic and proteomic evidence continues to grow at ever-increasing rates, while annotation efforts struggle to keep pace. A surprisingly small fraction of human genes have clear, documented associations with specific functions, and new functions continue to be found for characterized genes. Here we assembled an integrated collection of diverse genomic and proteomic data for 21,341 human genes and make quantitative associations of each to 4333 Gene Ontology terms. We combined guilt-by-profiling and guilt-by-association approaches to exploit features unique to the data types. Performance was evaluated by cross-validation, prospective validation, and by manual evaluation with the biological literature. Functional-linkage networks were also constructed, and their utility was demonstrated by identifying candidate genes related to a glioma FLN using a seed network from genome-wide association studies. Our annotations are presented-alongside existing validated annotations-in a publicly accessible and searchable web interface.

Functional Annotation of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture.

PubMed

Macqueen, Daniel J; Primmer, Craig R; Houston, Ross D; Nowak, Barbara F; Bernatchez, Louis; Bergseth, Steinar; Davidson, William S; Gallardo-Escárate, Cristian; Goldammer, Tom; Guiguen, Yann; Iturra, Patricia; Kijas, James W; Koop, Ben F; Lien, Sigbjørn; Maass, Alejandro; Martin, Samuel A M; McGinnity, Philip; Montecino, Martin; Naish, Kerry A; Nichols, Krista M; Ólafsson, Kristinn; Omholt, Stig W; Palti, Yniv; Plastow, Graham S; Rexroad, Caird E; Rise, Matthew L; Ritchie, Rachael J; Sandve, Simen R; Schulte, Patricia M; Tello, Alfredo; Vidal, Rodrigo; Vik, Jon Olav; Wargelius, Anna; Yáñez, José Manuel

2017-06-27

We describe an emerging initiative - the 'Functional Annotation of All Salmonid Genomes' (FAASG), which will leverage the extensive trait diversity that has evolved since a whole genome duplication event in the salmonid ancestor, to develop an integrative understanding of the functional genomic basis of phenotypic variation. The outcomes of FAASG will have diverse applications, ranging from improved understanding of genome evolution, to improving the efficiency and sustainability of aquaculture production, supporting the future of fundamental and applied research in an iconic fish lineage of major societal importance.

Current challenges in genome annotation through structural biology and bioinformatics.

PubMed

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

2012-10-01

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

GAP Final Technical Report 12-14-04

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrew J. Bordner, PhD, Senior Research Scientist

2004-12-14

The Genomics Annotation Platform (GAP) was designed to develop new tools for high throughput functional annotation and characterization of protein sequences and structures resulting from genomics and structural proteomics, benchmarking and application of those tools. Furthermore, this platform integrated the genomic scale sequence and structural analysis and prediction tools with the advanced structure prediction and bioinformatics environment of ICM. The development of GAP was primarily oriented towards the annotation of new biomolecular structures using both structural and sequence data. Even though the amount of protein X-ray crystal data is growing exponentially, the volume of sequence data is growing even moremore » rapidly. This trend was exploited by leveraging the wealth of sequence data to provide functional annotation for protein structures. The additional information provided by GAP is expected to assist the majority of the commercial users of ICM, who are involved in drug discovery, in identifying promising drug targets as well in devising strategies for the rational design of therapeutics directed at the protein of interest. The GAP also provided valuable tools for biochemistry education, and structural genomics centers. In addition, GAP incorporates many novel prediction and analysis methods not available in other molecular modeling packages. This development led to signing the first Molsoft agreement in the structural genomics annotation area with the University of oxford Structural Genomics Center. This commercial agreement validated the Molsoft efforts under the GAP project and provided the basis for further development of the large scale functional annotation platform.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2014-10-09

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

AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments

PubMed Central

Zheng, Jie; Stoyanovich, Julia; Manduchi, Elisabetta; Liu, Junmin; Stoeckert, Christian J.

2011-01-01

The ever-increasing scale of biological data sets, particularly those arising in the context of high-throughput technologies, requires the development of rich data exploration tools. In this article, we present AnnotCompute, an information discovery platform for repositories of functional genomics experiments such as ArrayExpress. Our system leverages semantic annotations of functional genomics experiments with controlled vocabulary and ontology terms, such as those from the MGED Ontology, to compute conceptual dissimilarities between pairs of experiments. These dissimilarities are then used to support two types of exploratory analysis—clustering and query-by-example. We show that our proposed dissimilarity measures correspond to a user's intuition about conceptual dissimilarity, and can be used to support effective query-by-example. We also evaluate the quality of clustering based on these measures. While AnnotCompute can support a richer data exploration experience, its effectiveness is limited in some cases, due to the quality of available annotations. Nonetheless, tools such as AnnotCompute may provide an incentive for richer annotations of experiments. Code is available for download at http://www.cbil.upenn.edu/downloads/AnnotCompute. Database URL: http://www.cbil.upenn.edu/annotCompute/ PMID:22190598

Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation

PubMed Central

Hardison, Ross C.

2017-01-01

Abstract The Roadmap Epigenomics Consortium has published whole-genome functional annotation maps in 127 human cell types by integrating data from studies of multiple epigenetic marks. These maps have been widely used for studying gene regulation in cell type-specific contexts and predicting the functional impact of DNA mutations on disease. Here, we present a new map of functional elements produced by applying a method called IDEAS on the same data. The method has several unique advantages and outperforms existing methods, including that used by the Roadmap Epigenomics Consortium. Using five categories of independent experimental datasets, we compared the IDEAS and Roadmap Epigenomics maps. While the overall concordance between the two maps is high, the maps differ substantially in the prediction details and in their consistency of annotation of a given genomic position across cell types. The annotation from IDEAS is uniformly more accurate than the Roadmap Epigenomics annotation and the improvement is substantial based on several criteria. We further introduce a pipeline that improves the reproducibility of functional annotation maps. Thus, we provide a high-quality map of candidate functional regions across 127 human cell types and compare the quality of different annotation methods in order to facilitate biomedical research in epigenomics. PMID:28973456

The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species.

PubMed

Childs, Kevin L; Konganti, Kranti; Buell, C Robin

2012-01-01

Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: http://bfgr.plantbiology.msu.edu.

Management and analysis of genomic functional and phenotypic controlled annotations to support biomedical investigation and practice.

PubMed

Masseroli, Marco

2007-07-01

The growing available genomic information provides new opportunities for novel research approaches and original biomedical applications that can provide effective data management and analysis support. In fact, integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. Here, we describe Genome Function INtegrated Discover (GFINDer), a Web-accessible three-tier multidatabase system we developed to automatically enrich lists of user-classified genes with several functional and phenotypic controlled annotations, and to statistically evaluate them in order to identify annotation categories significantly over- or underrepresented in each considered gene class. Genomic controlled annotations from Gene Ontology (GO), KEGG, Pfam, InterPro, and Online Mendelian Inheritance in Man (OMIM) were integrated in GFINDer and several categorical tests were implemented for their analysis. A controlled vocabulary of inherited disorder phenotypes was obtained by normalizing and hierarchically structuring disease accompanying signs and symptoms from OMIM Clinical Synopsis sections. GFINDer modular architecture is well suited for further system expansion and for sustaining increasing workload. Testing results showed that GFINDer analyses can highlight gene functional and phenotypic characteristics and differences, demonstrating its value in supporting genomic biomedical approaches aiming at understanding the complex biomolecular mechanisms underlying patho-physiological phenotypes, and in helping the transfer of genomic results to medical practice.

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

USDA-ARS?s Scientific Manuscript database

Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ansong, Charles; Tolic, Nikola; Purvine, Samuel O.

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify codingmore » regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.« less

CuGene as a tool to view and explore genomic data

NASA Astrophysics Data System (ADS)

Haponiuk, Michał; Pawełkowicz, Magdalena; Przybecki, Zbigniew; Nowak, Robert M.

2017-08-01

Integrated CuGene is an easy-to-use, open-source, on-line tool that can be used to browse, analyze, and query genomic data and annotations. It places annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. It also allows users to upload and display their own experimental results or annotation sets. An important functionality of the application is a possibility to find similarity between sequences by applying four different algorithms of different accuracy. The presented tool was tested on real genomic data and is extensively used by Polish Consortium of Cucumber Genome Sequencing.

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/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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

PubMed Central

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

2017-01-01

Abstract 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. PMID:28100699

Comparative genomics approaches to understanding and manipulating plant metabolism.

PubMed

Bradbury, Louis M T; Niehaus, Tom D; Hanson, Andrew D

2013-04-01

Over 3000 genomes, including numerous plant genomes, are now sequenced. However, their annotation remains problematic as illustrated by the many conserved genes with no assigned function, vague annotations such as 'kinase', or even wrong ones. Around 40% of genes of unknown function that are conserved between plants and microbes are probably metabolic enzymes or transporters; finding functions for these genes is a major challenge. Comparative genomics has correctly predicted functions for many such genes by analyzing genomic context, and gene fusions, distributions and co-expression. Comparative genomics complements genetic and biochemical approaches to dissect metabolism, continues to increase in power and decrease in cost, and has a pivotal role in modeling and engineering by helping identify functions for all metabolic genes. Copyright © 2012 Elsevier Ltd. All rights reserved.

GAMOLA2, a Comprehensive Software Package for the Annotation and Curation of Draft and Complete Microbial Genomes

PubMed Central

Altermann, Eric; Lu, Jingli; McCulloch, Alan

2017-01-01

Expert curated annotation remains one of the critical steps in achieving a reliable biological relevant annotation. Here we announce the release of GAMOLA2, a user friendly and comprehensive software package to process, annotate and curate draft and complete bacterial, archaeal, and viral genomes. GAMOLA2 represents a wrapping tool to combine gene model determination, functional Blast, COG, Pfam, and TIGRfam analyses with structural predictions including detection of tRNAs, rRNA genes, non-coding RNAs, signal protein cleavage sites, transmembrane helices, CRISPR repeats and vector sequence contaminations. GAMOLA2 has already been validated in a wide range of bacterial and archaeal genomes, and its modular concept allows easy addition of further functionality in future releases. A modified and adapted version of the Artemis Genome Viewer (Sanger Institute) has been developed to leverage the additional features and underlying information provided by the GAMOLA2 analysis, and is part of the software distribution. In addition to genome annotations, GAMOLA2 features, among others, supplemental modules that assist in the creation of custom Blast databases, annotation transfers between genome versions, and the preparation of Genbank files for submission via the NCBI Sequin tool. GAMOLA2 is intended to be run under a Linux environment, whereas the subsequent visualization and manual curation in Artemis is mobile and platform independent. The development of GAMOLA2 is ongoing and community driven. New functionality can easily be added upon user requests, ensuring that GAMOLA2 provides information relevant to microbiologists. The software is available free of charge for academic use. PMID:28386247

GAMOLA2, a Comprehensive Software Package for the Annotation and Curation of Draft and Complete Microbial Genomes.

PubMed

Altermann, Eric; Lu, Jingli; McCulloch, Alan

2017-01-01

Expert curated annotation remains one of the critical steps in achieving a reliable biological relevant annotation. Here we announce the release of GAMOLA2, a user friendly and comprehensive software package to process, annotate and curate draft and complete bacterial, archaeal, and viral genomes. GAMOLA2 represents a wrapping tool to combine gene model determination, functional Blast, COG, Pfam, and TIGRfam analyses with structural predictions including detection of tRNAs, rRNA genes, non-coding RNAs, signal protein cleavage sites, transmembrane helices, CRISPR repeats and vector sequence contaminations. GAMOLA2 has already been validated in a wide range of bacterial and archaeal genomes, and its modular concept allows easy addition of further functionality in future releases. A modified and adapted version of the Artemis Genome Viewer (Sanger Institute) has been developed to leverage the additional features and underlying information provided by the GAMOLA2 analysis, and is part of the software distribution. In addition to genome annotations, GAMOLA2 features, among others, supplemental modules that assist in the creation of custom Blast databases, annotation transfers between genome versions, and the preparation of Genbank files for submission via the NCBI Sequin tool. GAMOLA2 is intended to be run under a Linux environment, whereas the subsequent visualization and manual curation in Artemis is mobile and platform independent. The development of GAMOLA2 is ongoing and community driven. New functionality can easily be added upon user requests, ensuring that GAMOLA2 provides information relevant to microbiologists. The software is available free of charge for academic use.

PLAZA 3.0: an access point for plant comparative genomics

PubMed Central

Proost, Sebastian; Van Bel, Michiel; Vaneechoutte, Dries; Van de Peer, Yves; Inzé, Dirk; Mueller-Roeber, Bernd; Vandepoele, Klaas

2015-01-01

Comparative sequence analysis has significantly altered our view on the complexity of genome organization and gene functions in different kingdoms. PLAZA 3.0 is designed to make comparative genomics data for plants available through a user-friendly web interface. Structural and functional annotation, gene families, protein domains, phylogenetic trees and detailed information about genome organization can easily be queried and visualized. Compared with the first version released in 2009, which featured nine organisms, the number of integrated genomes is more than four times higher, and now covers 37 plant species. The new species provide a wider phylogenetic range as well as a more in-depth sampling of specific clades, and genomes of additional crop species are present. The functional annotation has been expanded and now comprises data from Gene Ontology, MapMan, UniProtKB/Swiss-Prot, PlnTFDB and PlantTFDB. Furthermore, we improved the algorithms to transfer functional annotation from well-characterized plant genomes to other species. The additional data and new features make PLAZA 3.0 (http://bioinformatics.psb.ugent.be/plaza/) a versatile and comprehensible resource for users wanting to explore genome information to study different aspects of plant biology, both in model and non-model organisms. PMID:25324309

The Proteome Folding Project: Proteome-scale prediction of structure and function

PubMed Central

Drew, Kevin; Winters, Patrick; Butterfoss, Glenn L.; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David R.; Davis, Trisha N.; Shasha, Dennis; Malmström, Lars; Bonneau, Richard

2011-01-01

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions. PMID:21824995

TriAnnot: A Versatile and High Performance Pipeline for the Automated Annotation of Plant Genomes

PubMed Central

Leroy, Philippe; Guilhot, Nicolas; Sakai, Hiroaki; Bernard, Aurélien; Choulet, Frédéric; Theil, Sébastien; Reboux, Sébastien; Amano, Naoki; Flutre, Timothée; Pelegrin, Céline; Ohyanagi, Hajime; Seidel, Michael; Giacomoni, Franck; Reichstadt, Mathieu; Alaux, Michael; Gicquello, Emmanuelle; Legeai, Fabrice; Cerutti, Lorenzo; Numa, Hisataka; Tanaka, Tsuyoshi; Mayer, Klaus; Itoh, Takeshi; Quesneville, Hadi; Feuillet, Catherine

2012-01-01

In support of the international effort to obtain a reference sequence of the bread wheat genome and to provide plant communities dealing with large and complex genomes with a versatile, easy-to-use online automated tool for annotation, we have developed the TriAnnot pipeline. Its modular architecture allows for the annotation and masking of transposable elements, the structural, and functional annotation of protein-coding genes with an evidence-based quality indexing, and the identification of conserved non-coding sequences and molecular markers. The TriAnnot pipeline is parallelized on a 712 CPU computing cluster that can run a 1-Gb sequence annotation in less than 5 days. It is accessible through a web interface for small scale analyses or through a server for large scale annotations. The performance of TriAnnot was evaluated in terms of sensitivity, specificity, and general fitness using curated reference sequence sets from rice and wheat. In less than 8 h, TriAnnot was able to predict more than 83% of the 3,748 CDS from rice chromosome 1 with a fitness of 67.4%. On a set of 12 reference Mb-sized contigs from wheat chromosome 3B, TriAnnot predicted and annotated 93.3% of the genes among which 54% were perfectly identified in accordance with the reference annotation. It also allowed the curation of 12 genes based on new biological evidences, increasing the percentage of perfect gene prediction to 63%. TriAnnot systematically showed a higher fitness than other annotation pipelines that are not improved for wheat. As it is easily adaptable to the annotation of other plant genomes, TriAnnot should become a useful resource for the annotation of large and complex genomes in the future. PMID:22645565

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 evolution as compared to 4.1% across the entire genome. Conclusions This extensive annotation dramatically extends the genome-based knowledge of the molecular genetics and structure of a major portion of the porcine immunome. Our complementary functional approach using co-expression during immune response has provided new putative immune response annotation for over 500 porcine genes. Our phylogenetic analysis of this core immunome cluster confirms rapid evolutionary change in this set of genes, and that, as in other species, such genes are important components of the pig’s adaptation to pathogen challenge over evolutionary time. These comprehensive and integrated analyses increase the value of the porcine genome sequence and provide important tools for global analyses and data-mining of the porcine immune response. PMID:23676093

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

2017-03-17

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. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of functional elements and regulatory circuits by Drosophila modENCODE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Sushmita; Ernst, Jason; Kharchenko, Peter V.

2010-12-22

To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- andmore » tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation. Several years after the complete genetic sequencing of many species, it is still unclear how to translate genomic information into a functional map of cellular and developmental programs. The Encyclopedia of DNA Elements (ENCODE) (1) and model organism ENCODE (modENCODE) (2) projects use diverse genomic assays to comprehensively annotate the Homo sapiens (human), Drosophila melanogaster (fruit fly), and Caenorhabditis elegans (worm) genomes, through systematic generation and computational integration of functional genomic data sets. Previous genomic studies in flies have made seminal contributions to our understanding of basic biological mechanisms and genome functions, facilitated by genetic, experimental, computational, and manual annotation of the euchromatic and heterochromatic genome (3), small genome size, short life cycle, and a deep knowledge of development, gene function, and chromosome biology. The functions of {approx}40% of the protein and nonprotein-coding genes [FlyBase 5.12 (4)] have been determined from cDNA collections (5, 6), manual curation of gene models (7), gene mutations and comprehensive genome-wide RNA interference screens (8-10), and comparative genomic analyses (11, 12). The Drosophila modENCODE project has generated more than 700 data sets that profile transcripts, histone modifications and physical nucleosome properties, general and specific transcription factors (TFs), and replication programs in cell lines, isolated tissues, and whole organisms across several developmental stages (Fig. 1). Here, we computationally integrate these data sets and report (i) improved and additional genome annotations, including full-length proteincoding genes and peptides as short as 21 amino acids; (ii) noncoding transcripts, including 132 candidate structural RNAs and 1608 nonstructural transcripts; (iii) additional Argonaute (Ago)-associated small RNA genes and pathways, including new microRNAs (miRNAs) encoded within protein-coding exons and endogenous small interfering RNAs (siRNAs) from 3-inch untranslated regions; (iv) chromatin 'states' defined by combinatorial patterns of 18 chromatin marks that are associated with distinct functions and properties; (v) regions of high TF occupancy and replication activity with likely epigenetic regulation; (vi)mixed TF and miRNA regulatory networks with hierarchical structure and enriched feed-forward loops; (vii) coexpression- and co-regulation-based functional annotations for nearly 3000 genes; (viii) stage- and tissue-specific regulators; and (ix) predictive models of gene expression levels and regulator function.« less

A curated catalog of canine and equine keratin genes

PubMed Central

Pujar, Shashikant; McGarvey, Kelly M.; Welle, Monika; Galichet, Arnaud; Müller, Eliane J.; Pruitt, Kim D.; Leeb, Tosso

2017-01-01

Keratins represent a large protein family with essential structural and functional roles in epithelial cells of skin, hair follicles, and other organs. During evolution the genes encoding keratins have undergone multiple rounds of duplication and humans have two clusters with a total of 55 functional keratin genes in their genomes. Due to the high similarity between different keratin paralogs and species-specific differences in gene content, the currently available keratin gene annotation in species with draft genome assemblies such as dog and horse is still imperfect. We compared the National Center for Biotechnology Information (NCBI) (dog annotation release 103, horse annotation release 101) and Ensembl (release 87) gene predictions for the canine and equine keratin gene clusters to RNA-seq data that were generated from adult skin of five dogs and two horses and from adult hair follicle tissue of one dog. Taking into consideration the knowledge on the conserved exon/intron structure of keratin genes, we annotated 61 putatively functional keratin genes in both the dog and horse, respectively. Subsequently, curators in the RefSeq group at NCBI reviewed their annotation of keratin genes in the dog and horse genomes (Annotation Release 104 and Annotation Release 102, respectively) and updated annotation and gene nomenclature of several keratin genes. The updates are now available in the NCBI Gene database (https://www.ncbi.nlm.nih.gov/gene). PMID:28846680

CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences

PubMed Central

2012-01-01

Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas. PMID:23256920

A Transcriptome Map of Actinobacillus pleuropneumoniae at Single-Nucleotide Resolution Using Deep RNA-Seq

PubMed Central

Su, Zhipeng; Zhu, Jiawen; Xu, Zhuofei; Xiao, Ran; Zhou, Rui; Li, Lu; Chen, Huanchun

2016-01-01

Actinobacillus pleuropneumoniae is the pathogen of porcine contagious pleuropneumoniae, a highly contagious respiratory disease of swine. Although the genome of A. pleuropneumoniae was sequenced several years ago, limited information is available on the genome-wide transcriptional analysis to accurately annotate the gene structures and regulatory elements. High-throughput RNA sequencing (RNA-seq) has been applied to study the transcriptional landscape of bacteria, which can efficiently and accurately identify gene expression regions and unknown transcriptional units, especially small non-coding RNAs (sRNAs), UTRs and regulatory regions. The aim of this study is to comprehensively analyze the transcriptome of A. pleuropneumoniae by RNA-seq in order to improve the existing genome annotation and promote our understanding of A. pleuropneumoniae gene structures and RNA-based regulation. In this study, we utilized RNA-seq to construct a single nucleotide resolution transcriptome map of A. pleuropneumoniae. More than 3.8 million high-quality reads (average length ~90 bp) from a cDNA library were generated and aligned to the reference genome. We identified 32 open reading frames encoding novel proteins that were mis-annotated in the previous genome annotations. The start sites for 35 genes based on the current genome annotation were corrected. Furthermore, 51 sRNAs in the A. pleuropneumoniae genome were discovered, of which 40 sRNAs were never reported in previous studies. The transcriptome map also enabled visualization of 5'- and 3'-UTR regions, in which contained 11 sRNAs. In addition, 351 operons covering 1230 genes throughout the whole genome were identified. The RNA-Seq based transcriptome map validated annotated genes and corrected annotations of open reading frames in the genome, and led to the identification of many functional elements (e.g. regions encoding novel proteins, non-coding sRNAs and operon structures). The transcriptional units described in this study provide a foundation for future studies concerning the gene functions and the transcriptional regulatory architectures of this pathogen. PMID:27018591

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

PubMed Central

Itoh, Takeshi; Tanaka, Tsuyoshi; Barrero, Roberto A.; Yamasaki, Chisato; Fujii, Yasuyuki; Hilton, Phillip B.; Antonio, Baltazar A.; Aono, Hideo; Apweiler, Rolf; Bruskiewich, Richard; Bureau, Thomas; Burr, Frances; Costa de Oliveira, Antonio; Fuks, Galina; Habara, Takuya; Haberer, Georg; Han, Bin; Harada, Erimi; Hiraki, Aiko T.; Hirochika, Hirohiko; Hoen, Douglas; Hokari, Hiroki; Hosokawa, Satomi; Hsing, Yue; Ikawa, Hiroshi; Ikeo, Kazuho; Imanishi, Tadashi; Ito, Yukiyo; Jaiswal, Pankaj; Kanno, Masako; Kawahara, Yoshihiro; Kawamura, Toshiyuki; Kawashima, Hiroaki; Khurana, Jitendra P.; Kikuchi, Shoshi; Komatsu, Setsuko; Koyanagi, Kanako O.; Kubooka, Hiromi; Lieberherr, Damien; Lin, Yao-Cheng; Lonsdale, David; Matsumoto, Takashi; Matsuya, Akihiro; McCombie, W. Richard; Messing, Joachim; Miyao, Akio; Mulder, Nicola; Nagamura, Yoshiaki; Nam, Jongmin; Namiki, Nobukazu; Numa, Hisataka; Nurimoto, Shin; O’Donovan, Claire; Ohyanagi, Hajime; Okido, Toshihisa; OOta, Satoshi; Osato, Naoki; Palmer, Lance E.; Quetier, Francis; Raghuvanshi, Saurabh; Saichi, Naomi; Sakai, Hiroaki; Sakai, Yasumichi; Sakata, Katsumi; Sakurai, Tetsuya; Sato, Fumihiko; Sato, Yoshiharu; Schoof, Heiko; Seki, Motoaki; Shibata, Michie; Shimizu, Yuji; Shinozaki, Kazuo; Shinso, Yuji; Singh, Nagendra K.; Smith-White, Brian; Takeda, Jun-ichi; Tanino, Motohiko; Tatusova, Tatiana; Thongjuea, Supat; Todokoro, Fusano; Tsugane, Mika; Tyagi, Akhilesh K.; Vanavichit, Apichart; Wang, Aihui; Wing, Rod A.; Yamaguchi, Kaori; Yamamoto, Mayu; Yamamoto, Naoyuki; Yu, Yeisoo; Zhang, Hao; Zhao, Qiang; Higo, Kenichi; Burr, Benjamin; Gojobori, Takashi; Sasaki, Takuji

2007-01-01

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ∼32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene. PMID:17210932

Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

PubMed Central

Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

2014-01-01

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website. PMID:24778629

PLAZA 3.0: an access point for plant comparative genomics.

PubMed

Proost, Sebastian; Van Bel, Michiel; Vaneechoutte, Dries; Van de Peer, Yves; Inzé, Dirk; Mueller-Roeber, Bernd; Vandepoele, Klaas

2015-01-01

Comparative sequence analysis has significantly altered our view on the complexity of genome organization and gene functions in different kingdoms. PLAZA 3.0 is designed to make comparative genomics data for plants available through a user-friendly web interface. Structural and functional annotation, gene families, protein domains, phylogenetic trees and detailed information about genome organization can easily be queried and visualized. Compared with the first version released in 2009, which featured nine organisms, the number of integrated genomes is more than four times higher, and now covers 37 plant species. The new species provide a wider phylogenetic range as well as a more in-depth sampling of specific clades, and genomes of additional crop species are present. The functional annotation has been expanded and now comprises data from Gene Ontology, MapMan, UniProtKB/Swiss-Prot, PlnTFDB and PlantTFDB. Furthermore, we improved the algorithms to transfer functional annotation from well-characterized plant genomes to other species. The additional data and new features make PLAZA 3.0 (http://bioinformatics.psb.ugent.be/plaza/) a versatile and comprehensible resource for users wanting to explore genome information to study different aspects of plant biology, both in model and non-model organisms. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts

PubMed Central

Aubourg, Sébastien; Brunaud, Véronique; Bruyère, Clémence; Cock, Mark; Cooke, Richard; Cottet, Annick; Couloux, Arnaud; Déhais, Patrice; Deléage, Gilbert; Duclert, Aymeric; Echeverria, Manuel; Eschbach, Aimée; Falconet, Denis; Filippi, Ghislain; Gaspin, Christine; Geourjon, Christophe; Grienenberger, Jean-Michel; Houlné, Guy; Jamet, Elisabeth; Lechauve, Frédéric; Leleu, Olivier; Leroy, Philippe; Mache, Régis; Meyer, Christian; Nedjari, Hafed; Negrutiu, Ioan; Orsini, Valérie; Peyretaillade, Eric; Pommier, Cyril; Raes, Jeroen; Risler, Jean-Loup; Rivière, Stéphane; Rombauts, Stéphane; Rouzé, Pierre; Schneider, Michel; Schwob, Philippe; Small, Ian; Soumayet-Kampetenga, Ghislain; Stankovski, Darko; Toffano, Claire; Tognolli, Michael; Caboche, Michel; Lecharny, Alain

2005-01-01

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Prot. PMID:15608279

Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

PubMed

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

2016-08-01

Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.

Year 2 Report: Protein Function Prediction Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Brassica database (BRAD) version 2.0: integrating and mining Brassicaceae species genomic resources.

PubMed

Wang, Xiaobo; Wu, Jian; Liang, Jianli; Cheng, Feng; Wang, Xiaowu

2015-01-01

The Brassica database (BRAD) was built initially to assist users apply Brassica rapa and Arabidopsis thaliana genomic data efficiently to their research. However, many Brassicaceae genomes have been sequenced and released after its construction. These genomes are rich resources for comparative genomics, gene annotation and functional evolutionary studies of Brassica crops. Therefore, we have updated BRAD to version 2.0 (V2.0). In BRAD V2.0, 11 more Brassicaceae genomes have been integrated into the database, namely those of Arabidopsis lyrata, Aethionema arabicum, Brassica oleracea, Brassica napus, Camelina sativa, Capsella rubella, Leavenworthia alabamica, Sisymbrium irio and three extremophiles Schrenkiella parvula, Thellungiella halophila and Thellungiella salsuginea. BRAD V2.0 provides plots of syntenic genomic fragments between pairs of Brassicaceae species, from the level of chromosomes to genomic blocks. The Generic Synteny Browser (GBrowse_syn), a module of the Genome Browser (GBrowse), is used to show syntenic relationships between multiple genomes. Search functions for retrieving syntenic and non-syntenic orthologs, as well as their annotation and sequences are also provided. Furthermore, genome and annotation information have been imported into GBrowse so that all functional elements can be visualized in one frame. We plan to continually update BRAD by integrating more Brassicaceae genomes into the database. Database URL: http://brassicadb.org/brad/. © The Author(s) 2015. Published by Oxford University Press.

RNA-Seq Based Transcriptional Map of Bovine Respiratory Disease Pathogen “Histophilus somni 2336”

PubMed Central

Kumar, Ranjit; Lawrence, Mark L.; Watt, James; Cooksey, Amanda M.; Burgess, Shane C.; Nanduri, Bindu

2012-01-01

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify “novel” genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method. The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (∼30%) were located in genomic region unique to strain 2336 (∼18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations. PMID:22276113

RNA-seq based transcriptional map of bovine respiratory disease pathogen "Histophilus somni 2336".

PubMed

Kumar, Ranjit; Lawrence, Mark L; Watt, James; Cooksey, Amanda M; Burgess, Shane C; Nanduri, Bindu

2012-01-01

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify "novel" genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method.The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (∼30%) were located in genomic region unique to strain 2336 (∼18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations.

Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rutledge, Alexandra C.; Jones, Marcus B.; Chauhan, Sadhana

2012-03-27

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. To date, the perceived value of manual curation for genome annotations is not offset by the real cost and time associated with the process. In order to balance the large number of sequences generated, the annotation process is now performed almost exclusively in an automated fashion for most genome sequencing projects. One possible way to reduce errors inherent to automated computational annotations is to apply data from 'omics' measurements (i.e. transcriptional and proteomic) to themore » un-annotated genome with a proteogenomic-based approach. This approach does require additional experimental and bioinformatics methods to include omics technologies; however, the approach is readily automatable and can benefit from rapid developments occurring in those research domains as well. The annotation process can be improved by experimental validation of transcription and translation and aid in the discovery of annotation errors. Here the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species, as is becoming common in sequencing efforts. Transcriptomic and proteomic data derived from three highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 previously incorrect protein-coding sequences (e.g., observed frameshifts, extended start sites, and translated pseudogenes) within the three current Yersinia genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes 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, and a transcriptional regulator, among other proteins, most of which are annotated as hypothetical, that were missed during annotation.« less

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment.

PubMed

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-09-01

The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org.

IMG 4 version of the integrated microbial genomes comparative analysis system

PubMed Central

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N.; Kyrpides, Nikos C.

2014-01-01

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu). PMID:24165883

IMG 4 version of the integrated microbial genomes comparative analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Finally, different IMG datamarts providemore » support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).« less

IMG 4 version of the integrated microbial genomes comparative analysis system.

PubMed

Markowitz, Victor M; Chen, I-Min A; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N; Kyrpides, Nikos C

2014-01-01

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG's data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG's annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.

PubMed

Karchin, Rachel; Diekhans, Mark; Kelly, Libusha; Thomas, Daryl J; Pieper, Ursula; Eswar, Narayanan; Haussler, David; Sali, Andrej

2005-06-15

The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org http://salilab.org/LS-SNP/supp-info.pdf.

Complete Chloroplast Genome Sequence and Annotation of the Tropical japonica Group of Asian Cultivated Rice (Oryza sativa L.)

PubMed Central

Wang, Shuo

2016-01-01

We announce here the first complete chloroplast genome sequence of the tropical japonica rice, along with its genome structure and functional annotation. The plant was collected from Indonesia and deposited as a germplasm accession of the International Rice GenBank Collection (IRGC 66630) at the International Rice Research Institute (IRRI). This genome provides valuable data for the future utilization of the germplasm of rice. PMID:26893422

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

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system.

PubMed

Chen, I-Min A; Markowitz, Victor M; Palaniappan, Krishna; Szeto, Ernest; Chu, Ken; Huang, Jinghua; Ratner, Anna; Pillay, Manoj; Hadjithomas, Michalis; Huntemann, Marcel; Mikhailova, Natalia; Ovchinnikova, Galina; Ivanova, Natalia N; Kyrpides, Nikos C

2016-04-26

The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.

SG-ADVISER CNV: copy-number variant annotation and interpretation.

PubMed

Erikson, Galina A; Deshpande, Neha; Kesavan, Balachandar G; Torkamani, Ali

2015-09-01

Copy-number variants have been associated with a variety of diseases, especially cancer, autism, schizophrenia, and developmental delay. The majority of clinically relevant events occur de novo, necessitating the interpretation of novel events. In this light, we present the Scripps Genome ADVISER CNV annotation pipeline and Web server, which aims to fill the gap between copy number variant detection and interpretation by performing in-depth annotations and functional predictions for copy number variants. The Scripps Genome ADVISER CNV suite includes a Web server interface to a high-performance computing environment for calculations of annotations and a table-based user interface that allows for the execution of numerous annotation-based variant filtration strategies and statistics. The annotation results include details regarding location, impact on the coding portion of genes, allele frequency information (including allele frequencies from the Scripps Wellderly cohort), and overlap information with other reference data sets (including ClinVar, DGV, DECIPHER). A summary variant classification is produced (ADVISER score) based on the American College of Medical Genetics and Genomics scoring guidelines. We demonstrate >90% sensitivity/specificity for detection of pathogenic events. Scripps Genome ADVISER CNV is designed to allow users with no prior bioinformatics expertise to manipulate large volumes of copy-number variant data. Scripps Genome ADVISER CNV is available at http://genomics.scripps.edu/ADVISER/.

A post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs.

PubMed

Swain, Martin T; Tsai, Isheng J; Assefa, Samual A; Newbold, Chris; Berriman, Matthew; Otto, Thomas D

2012-06-07

Genome projects now produce draft assemblies within weeks owing to advanced high-throughput sequencing technologies. For milestone projects such as Escherichia coli or Homo sapiens, teams of scientists were employed to manually curate and finish these genomes to a high standard. Nowadays, this is not feasible for most projects, and the quality of genomes is generally of a much lower standard. This protocol describes software (PAGIT) that is used to improve the quality of draft genomes. It offers flexible functionality to close gaps in scaffolds, correct base errors in the consensus sequence and exploit reference genomes (if available) in order to improve scaffolding and generating annotations. The protocol is most accessible for bacterial and small eukaryotic genomes (up to 300 Mb), such as pathogenic bacteria, malaria and parasitic worms. Applying PAGIT to an E. coli assembly takes ∼24 h: it doubles the average contig size and annotates over 4,300 gene models.

Sheep genome functional annotation reveals proximal regulatory elements contributed to the evolution of modern breeds.

PubMed

Naval-Sanchez, Marina; Nguyen, Quan; McWilliam, Sean; Porto-Neto, Laercio R; Tellam, Ross; Vuocolo, Tony; Reverter, Antonio; Perez-Enciso, Miguel; Brauning, Rudiger; Clarke, Shannon; McCulloch, Alan; Zamani, Wahid; Naderi, Saeid; Rezaei, Hamid Reza; Pompanon, Francois; Taberlet, Pierre; Worley, Kim C; Gibbs, Richard A; Muzny, Donna M; Jhangiani, Shalini N; Cockett, Noelle; Daetwyler, Hans; Kijas, James

2018-02-28

Domestication fundamentally reshaped animal morphology, physiology and behaviour, offering the opportunity to investigate the molecular processes driving evolutionary change. Here we assess sheep domestication and artificial selection by comparing genome sequence from 43 modern breeds (Ovis aries) and their Asian mouflon ancestor (O. orientalis) to identify selection sweeps. Next, we provide a comparative functional annotation of the sheep genome, validated using experimental ChIP-Seq of sheep tissue. Using these annotations, we evaluate the impact of selection and domestication on regulatory sequences and find that sweeps are significantly enriched for protein coding genes, proximal regulatory elements of genes and genome features associated with active transcription. Finally, we find individual sites displaying strong allele frequency divergence are enriched for the same regulatory features. Our data demonstrate that remodelling of gene expression is likely to have been one of the evolutionary forces that drove phenotypic diversification of this common livestock species.

Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

PubMed

Nowrousian, Minou; Würtz, Christian; Pöggeler, Stefanie; Kück, Ulrich

2004-03-01

One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes.

PubMed

Zhang, Jia; Yang, Ming-Kun; Zeng, Honghui; Ge, Feng

2016-11-01

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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 justifiable biological basis. PMID:22359495

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.

Optimizing high performance computing workflow for protein functional annotation

PubMed Central

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

2014-01-01

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. PMID:25313296

Complete Chloroplast Genome Sequence and Annotation of the Tropical japonica Group of Asian Cultivated Rice (Oryza sativa L.).

PubMed

Wang, Shuo; Gao, Li-Zhi

2016-02-18

We announce here the first complete chloroplast genome sequence of the tropical japonica rice, along with its genome structure and functional annotation. The plant was collected from Indonesia and deposited as a germplasm accession of the International Rice GenBank Collection (IRGC 66630) at the International Rice Research Institute (IRRI). This genome provides valuable data for the future utilization of the germplasm of rice. Copyright © 2016 Wang and Gao.

Reduce Manual Curation by Combining Gene Predictions from Multiple Annotation Engines, a Case Study of Start Codon Prediction

PubMed Central

Ederveen, Thomas H. A.; Overmars, Lex; van Hijum, Sacha A. F. T.

2013-01-01

Nowadays, prokaryotic genomes are sequenced faster than the capacity to manually curate gene annotations. Automated genome annotation engines provide users a straight-forward and complete solution for predicting ORF coordinates and function. For many labs, the use of AGEs is therefore essential to decrease the time necessary for annotating a given prokaryotic genome. However, it is not uncommon for AGEs to provide different and sometimes conflicting predictions. Combining multiple AGEs might allow for more accurate predictions. Here we analyzed the ab initio open reading frame (ORF) calling performance of different AGEs based on curated genome annotations of eight strains from different bacterial species with GC% ranging from 35–52%. We present a case study which demonstrates a novel way of comparative genome annotation, using combinations of AGEs in a pre-defined order (or path) to predict ORF start codons. The order of AGE combinations is from high to low specificity, where the specificity is based on the eight genome annotations. For each AGE combination we are able to derive a so-called projected confidence value, which is the average specificity of ORF start codon prediction based on the eight genomes. The projected confidence enables estimating likeliness of a correct prediction for a particular ORF start codon by a particular AGE combination, pinpointing ORFs notoriously difficult to predict start codons. We correctly predict start codons for 90.5±4.8% of the genes in a genome (based on the eight genomes) with an accuracy of 81.1±7.6%. Our consensus-path methodology allows a marked improvement over majority voting (9.7±4.4%) and with an optimal path ORF start prediction sensitivity is gained while maintaining a high specificity. PMID:23675487

Sockeye: A 3D Environment for Comparative Genomics

PubMed Central

Montgomery, Stephen B.; Astakhova, Tamara; Bilenky, Mikhail; Birney, Ewan; Fu, Tony; Hassel, Maik; Melsopp, Craig; Rak, Marcin; Robertson, A. Gordon; Sleumer, Monica; Siddiqui, Asim S.; Jones, Steven J.M.

2004-01-01

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization. PMID:15123592

ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data

PubMed Central

2010-01-01

Background Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome. Results We have developed ChIPpeakAnno as a Bioconductor package within the statistical programming environment R to facilitate batch annotation of enriched peaks identified from ChIP-seq, ChIP-chip, cap analysis of gene expression (CAGE) or any experiments resulting in a large number of enriched genomic regions. The binding sites annotated with ChIPpeakAnno can be viewed easily as a table, a pie chart or plotted in histogram form, i.e., the distribution of distances to the nearest genes for each set of peaks. In addition, we have implemented functionalities for determining the significance of overlap between replicates or binding sites among transcription factors within a complex, and for drawing Venn diagrams to visualize the extent of the overlap between replicates. Furthermore, the package includes functionalities to retrieve sequences flanking putative binding sites for PCR amplification, cloning, or motif discovery, and to identify Gene Ontology (GO) terms associated with adjacent genes. Conclusions ChIPpeakAnno enables batch annotation of the binding sites identified from ChIP-seq, ChIP-chip, CAGE or any technology that results in a large number of enriched genomic regions within the statistical programming environment R. Allowing users to pass their own annotation data such as a different Chromatin immunoprecipitation (ChIP) preparation and a dataset from literature, or existing annotation packages, such as GenomicFeatures and BSgenome, provides flexibility. Tight integration to the biomaRt package enables up-to-date annotation retrieval from the BioMart database. PMID:20459804

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

PubMed Central

Damienikan, Aliaksandr U.

2016-01-01

The majority of bacterial genome annotations are currently automated and based on a ‘gene by gene’ approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows) open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators) in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB) and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp.) and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn’t fit with regulatory information allowed us to correct product and gene names for over 300 loci. PMID:27257541

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. © 2014 Wiley Periodicals, Inc.

Whole genome de novo sequencing and genome annotation of the world popular cultivated edible mushroom, Lentinula edodes.

PubMed

Shim, Donghwan; Park, Sin-Gi; Kim, Kangmin; Bae, Wonsil; Lee, Gir Won; Ha, Byeong-Suk; Ro, Hyeon-Su; Kim, Myungkil; Ryoo, Rhim; Rhee, Sung-Keun; Nou, Ill-Sup; Koo, Chang-Duck; Hong, Chang Pyo; Ryu, Hojin

2016-04-10

Lentinula edodes, the popular shiitake mushroom, is one of the most important cultivated edible mushrooms. It is used as a food and for medicinal purposes. Here, we present the 46.1 Mb draft genome of L. edodes, comprising 13,028 predicted gene models. The genome assembly consists of 31 scaffolds. Gene annotation provides key information about various signaling pathways and secondary metabolites. This genomic information should help establish the molecular genetic markers for MAS/MAB and increase our understanding of the genome structure and function. Copyright © 2016 Elsevier B.V. All rights reserved.

Variation resources at UC Santa Cruz.

PubMed

Thomas, Daryl J; Trumbower, Heather; Kern, Andrew D; Rhead, Brooke L; Kuhn, Robert M; Haussler, David; Kent, W James

2007-01-01

The variation resources within the University of California Santa Cruz Genome Browser include polymorphism data drawn from public collections and analyses of these data, along with their display in the context of other genomic annotations. Primary data from dbSNP is included for many organisms, with added information including genomic alleles and orthologous alleles for closely related organisms. Display filtering and coloring is available by variant type, functional class or other annotations. Annotation of potential errors is highlighted and a genomic alignment of the variant's flanking sequence is displayed. HapMap allele frequencies and linkage disequilibrium (LD) are available for each HapMap population, along with non-human primate alleles. The browsing and analysis tools, downloadable data files and links to documentation and other information can be found at http://genome.ucsc.edu/.

Dictionary-driven protein annotation.

PubMed

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

2002-09-01

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

Issues with RNA-seq analysis in non-model organisms: A salmonid example.

PubMed

Sundaram, Arvind; Tengs, Torstein; Grimholt, Unni

2017-10-01

High throughput sequencing (HTS) is useful for many purposes as exemplified by the other topics included in this special issue. The purpose of this paper is to look into the unique challenges of using this technology in non-model organisms where resources such as genomes, functional genome annotations or genome complexity provide obstacles not met in model organisms. To describe these challenges, we narrow our scope to RNA sequencing used to study differential gene expression in response to pathogen challenge. As a demonstration species we chose Atlantic salmon, which has a sequenced genome with poor annotation and an added complexity due to many duplicated genes. We find that our RNA-seq analysis pipeline deciphers between duplicates despite high sequence identity. However, annotation issues provide problems in linking differentially expressed genes to pathways. Also, comparing results between approaches and species are complicated due to lack of standardized annotation. Copyright © 2017 Elsevier Ltd. All rights reserved.

GAMES identifies and annotates mutations in next-generation sequencing projects.

PubMed

Sana, Maria Elena; Iascone, Maria; Marchetti, Daniela; Palatini, Jeff; Galasso, Marco; Volinia, Stefano

2011-01-01

Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users. We developed GAMES (Genomic Analysis of Mutations Extracted by Sequencing), a pipeline aiming to serve as an efficient middleman between data deluge and investigators. GAMES attains multiple levels of filtering and annotation, such as aligning the reads to a reference genome, performing quality control and mutational analysis, integrating results with genome annotations and sorting each mismatch/deletion according to a range of parameters. Variations are matched to known polymorphisms. The prediction of functional mutations is achieved by using different approaches. Overall GAMES enables an effective complexity reduction in large-scale DNA-sequencing projects. GAMES is available free of charge to academic users and may be obtained from http://aqua.unife.it/GAMES.

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment

PubMed Central

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z.; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-01-01

Summary: The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. Availability and Implementation: VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org. Contact: lukas.habegger@yale.edu or mark.gerstein@yale.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22743228

RICD: a rice indica cDNA database resource for rice functional genomics.

PubMed

Lu, Tingting; Huang, Xuehui; Zhu, Chuanrang; Huang, Tao; Zhao, Qiang; Xie, Kabing; Xiong, Lizhong; Zhang, Qifa; Han, Bin

2008-11-26

The Oryza sativa L. indica subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two indica varieties Guangluai 4 and Minghui 63. A database of the rice indica cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the indica cDNA clones. Rice Indica cDNA Database (RICD) is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB) and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA. The online rice indica cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of indica subspecies and for comparative genomics. The RICD database is available through our website http://www.ncgr.ac.cn/ricd.

AnnotateGenomicRegions: a web application.

PubMed

Zammataro, Luca; DeMolfetta, Rita; Bucci, Gabriele; Ceol, Arnaud; Muller, Heiko

2014-01-01

Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions.

AnnotateGenomicRegions: a web application

PubMed Central

2014-01-01

Background Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Results Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. Conclusions The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions. PMID:24564446

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data.

PubMed

Peterson, Elena S; McCue, Lee Ann; Schrimpe-Rutledge, Alexandra C; Jensen, Jeffrey L; Walker, Hyunjoo; Kobold, Markus A; Webb, Samantha R; Payne, Samuel H; Ansong, Charles; Adkins, Joshua N; Cannon, William R; Webb-Robertson, Bobbie-Jo M

2012-04-05

The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

PubMed Central

2012-01-01

Background The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. Results VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. Conclusions VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php. PMID:22480257

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

DOE PAGES

Chen, I-Min A.; Markowitz, Victor M.; Palaniappan, Krishna; ...

2016-04-26

Background: The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Results: Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existingmore » IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. Conclusion: By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.« less

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, I-Min A.; Markowitz, Victor M.; Palaniappan, Krishna

Background: The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Results: Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existingmore » IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. Conclusion: By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.« less

Improved Genome Assembly and Annotation for the Rock Pigeon (Columba livia)

PubMed Central

Holt, Carson; Campbell, Michael; Keays, David A.; Edelman, Nathaniel; Kapusta, Aurélie; Maclary, Emily; T. Domyan, Eric; Suh, Alexander; Warren, Wesley C.; Yandell, Mark; Gilbert, M. Thomas P.; Shapiro, Michael D.

2018-01-01

The domestic rock pigeon (Columba livia) is among the most widely distributed and phenotypically diverse avian species. C. livia is broadly studied in ecology, genetics, physiology, behavior, and evolutionary biology, and has recently emerged as a model for understanding the molecular basis of anatomical diversity, the magnetic sense, and other key aspects of avian biology. Here we report an update to the C. livia genome reference assembly and gene annotation dataset. Greatly increased scaffold lengths in the updated reference assembly, along with an updated annotation set, provide improved tools for evolutionary and functional genetic studies of the pigeon, and for comparative avian genomics in general. PMID:29519939

Caveat emptor: limitations of the automated reconstruction of metabolic pathways in Plasmodium.

PubMed

Ginsburg, Hagai

2009-01-01

The functional reconstruction of metabolic pathways from an annotated genome is a tedious and demanding enterprise. Automation of this endeavor using bioinformatics algorithms could cope with the ever-increasing number of sequenced genomes and accelerate the process. Here, the manual reconstruction of metabolic pathways in the functional genomic database of Plasmodium falciparum--Malaria Parasite Metabolic Pathways--is described and compared with pathways generated automatically as they appear in PlasmoCyc, metaSHARK and the Kyoto Encyclopedia for Genes and Genomes. A critical evaluation of this comparison discloses that the automatic reconstruction of pathways generates manifold paths that need an expert manual verification to accept some and reject most others based on manually curated gene annotation.

MicroScope—an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data

PubMed Central

Vallenet, David; Belda, Eugeni; Calteau, Alexandra; Cruveiller, Stéphane; Engelen, Stefan; Lajus, Aurélie; Le Fèvre, François; Longin, Cyrille; Mornico, Damien; Roche, David; Rouy, Zoé; Salvignol, Gregory; Scarpelli, Claude; Thil Smith, Adam Alexander; Weiman, Marion; Médigue, Claudine

2013-01-01

MicroScope is an integrated platform dedicated to both the methodical updating of microbial genome annotation and to comparative analysis. The resource provides data from completed and ongoing genome projects (automatic and expert annotations), together with data sources from post-genomic experiments (i.e. transcriptomics, mutant collections) allowing users to perfect and improve the understanding of gene functions. MicroScope (http://www.genoscope.cns.fr/agc/microscope) combines tools and graphical interfaces to analyse genomes and to perform the manual curation of gene annotations in a comparative context. Since its first publication in January 2006, the system (previously named MaGe for Magnifying Genomes) has been continuously extended both in terms of data content and analysis tools. The last update of MicroScope was published in 2009 in the Database journal. Today, the resource contains data for >1600 microbial genomes, of which ∼300 are manually curated and maintained by biologists (1200 personal accounts today). Expert annotations are continuously gathered in the MicroScope database (∼50 000 a year), contributing to the improvement of the quality of microbial genomes annotations. Improved data browsing and searching tools have been added, original tools useful in the context of expert annotation have been developed and integrated and the website has been significantly redesigned to be more user-friendly. Furthermore, in the context of the European project Microme (Framework Program 7 Collaborative Project), MicroScope is becoming a resource providing for the curation and analysis of both genomic and metabolic data. An increasing number of projects are related to the study of environmental bacterial (meta)genomes that are able to metabolize a large variety of chemical compounds that may be of high industrial interest. PMID:23193269

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.

MIPS: a database for genomes and protein sequences

PubMed Central

Mewes, H. W.; Frishman, D.; Güldener, U.; Mannhaupt, G.; Mayer, K.; Mokrejs, M.; Morgenstern, B.; Münsterkötter, M.; Rudd, S.; Weil, B.

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz–Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91–93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155–158; Barker et al. (2001) Nucleic Acids Res., 29, 29–32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de). PMID:11752246

MIPS: a database for genomes and protein sequences.

PubMed

Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

ABrowse--a customizable next-generation genome browser framework.

PubMed

Kong, Lei; Wang, Jun; Zhao, Shuqi; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2012-01-05

With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome has been built at http://arabidopsis.cbi.edu.cn/.

Web Apollo: a web-based genomic annotation editing platform.

PubMed

Lee, Eduardo; Helt, Gregg A; Reese, Justin T; Munoz-Torres, Monica C; Childers, Chris P; Buels, Robert M; Stein, Lincoln; Holmes, Ian H; Elsik, Christine G; Lewis, Suzanna E

2013-08-30

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.

Web Apollo: a web-based genomic annotation editing platform

PubMed Central

2013-01-01

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world. PMID:24000942

Proteomics informed by transcriptomics for characterising active transposable elements and genome annotation in Aedes aegypti.

PubMed

Maringer, Kevin; Yousuf, Amjad; Heesom, Kate J; Fan, Jun; Lee, David; Fernandez-Sesma, Ana; Bessant, Conrad; Matthews, David A; Davidson, Andrew D

2017-01-19

Aedes aegypti is a vector for the (re-)emerging human pathogens dengue, chikungunya, yellow fever and Zika viruses. Almost half of the Ae. aegypti genome is comprised of transposable elements (TEs). Transposons have been linked to diverse cellular processes, including the establishment of viral persistence in insects, an essential step in the transmission of vector-borne viruses. However, up until now it has not been possible to study the overall proteome derived from an organism's mobile genetic elements, partly due to the highly divergent nature of TEs. Furthermore, as for many non-model organisms, incomplete genome annotation has hampered proteomic studies on Ae. aegypti. We analysed the Ae. aegypti proteome using our new proteomics informed by transcriptomics (PIT) technique, which bypasses the need for genome annotation by identifying proteins through matched transcriptomic (rather than genomic) data. Our data vastly increase the number of experimentally confirmed Ae. aegypti proteins. The PIT analysis also identified hotspots of incomplete genome annotation, and showed that poor sequence and assembly quality do not explain all annotation gaps. Finally, in a proof-of-principle study, we developed criteria for the characterisation of proteomically active TEs. Protein expression did not correlate with a TE's genomic abundance at different levels of classification. Most notably, long terminal repeat (LTR) retrotransposons were markedly enriched compared to other elements. PIT was superior to 'conventional' proteomic approaches in both our transposon and genome annotation analyses. We present the first proteomic characterisation of an organism's repertoire of mobile genetic elements, which will open new avenues of research into the function of transposon proteins in health and disease. Furthermore, our study provides a proof-of-concept that PIT can be used to evaluate a genome's annotation to guide annotation efforts which has the potential to improve the efficiency of annotation projects in non-model organisms. PIT therefore represents a valuable new tool to study the biology of the important vector species Ae. aegypti, including its role in transmitting emerging viruses of global public health concern.

Towards a complete map of the human long non-coding RNA transcriptome.

PubMed

Uszczynska-Ratajczak, Barbara; Lagarde, Julien; Frankish, Adam; Guigó, Roderic; Johnson, Rory

2018-05-23

Gene maps, or annotations, enable us to navigate the functional landscape of our genome. They are a resource upon which virtually all studies depend, from single-gene to genome-wide scales and from basic molecular biology to medical genetics. Yet present-day annotations suffer from trade-offs between quality and size, with serious but often unappreciated consequences for downstream studies. This is particularly true for long non-coding RNAs (lncRNAs), which are poorly characterized compared to protein-coding genes. Long-read sequencing technologies promise to improve current annotations, paving the way towards a complete annotation of lncRNAs expressed throughout a human lifetime.

Design and implementation of a database for Brucella melitensis genome annotation.

PubMed

De Hertogh, Benoît; Lahlimi, Leïla; Lambert, Christophe; Letesson, Jean-Jacques; Depiereux, Eric

2008-03-18

The genome sequences of three Brucella biovars and of some species close to Brucella sp. have become available, leading to new relationship analysis. Moreover, the automatic genome annotation of the pathogenic bacteria Brucella melitensis has been manually corrected by a consortium of experts, leading to 899 modifications of start sites predictions among the 3198 open reading frames (ORFs) examined. This new annotation, coupled with the results of automatic annotation tools of the complete genome sequences of the B. melitensis genome (including BLASTs to 9 genomes close to Brucella), provides numerous data sets related to predicted functions, biochemical properties and phylogenic comparisons. To made these results available, alphaPAGe, a functional auto-updatable database of the corrected sequence genome of B. melitensis, has been built, using the entity-relationship (ER) approach and a multi-purpose database structure. A friendly graphical user interface has been designed, and users can carry out different kinds of information by three levels of queries: (1) the basic search use the classical keywords or sequence identifiers; (2) the original advanced search engine allows to combine (by using logical operators) numerous criteria: (a) keywords (textual comparison) related to the pCDS's function, family domains and cellular localization; (b) physico-chemical characteristics (numerical comparison) such as isoelectric point or molecular weight and structural criteria such as the nucleic length or the number of transmembrane helix (TMH); (c) similarity scores with Escherichia coli and 10 species phylogenetically close to B. melitensis; (3) complex queries can be performed by using a SQL field, which allows all queries respecting the database's structure. The database is publicly available through a Web server at the following url: http://www.fundp.ac.be/urbm/bioinfo/aPAGe.

Ensembl core software resources: storage and programmatic access for DNA sequence and genome annotation.

PubMed

Ruffier, Magali; Kähäri, Andreas; Komorowska, Monika; Keenan, Stephen; Laird, Matthew; Longden, Ian; Proctor, Glenn; Searle, Steve; Staines, Daniel; Taylor, Kieron; Vullo, Alessandro; Yates, Andrew; Zerbino, Daniel; Flicek, Paul

2017-01-01

The Ensembl software resources are a stable infrastructure to store, access and manipulate genome assemblies and their functional annotations. The Ensembl 'Core' database and Application Programming Interface (API) was our first major piece of software infrastructure and remains at the centre of all of our genome resources. Since its initial design more than fifteen years ago, the number of publicly available genomic, transcriptomic and proteomic datasets has grown enormously, accelerated by continuous advances in DNA-sequencing technology. Initially intended to provide annotation for the reference human genome, we have extended our framework to support the genomes of all species as well as richer assembly models. Cross-referenced links to other informatics resources facilitate searching our database with a variety of popular identifiers such as UniProt and RefSeq. Our comprehensive and robust framework storing a large diversity of genome annotations in one location serves as a platform for other groups to generate and maintain their own tailored annotation. We welcome reuse and contributions: our databases and APIs are publicly available, all of our source code is released with a permissive Apache v2.0 licence at http://github.com/Ensembl and we have an active developer mailing list ( http://www.ensembl.org/info/about/contact/index.html ). http://www.ensembl.org. © The Author(s) 2017. Published by Oxford University Press.

Improved Genome Assembly and Annotation for the Rock Pigeon (Columba livia).

PubMed

Holt, Carson; Campbell, Michael; Keays, David A; Edelman, Nathaniel; Kapusta, Aurélie; Maclary, Emily; T Domyan, Eric; Suh, Alexander; Warren, Wesley C; Yandell, Mark; Gilbert, M Thomas P; Shapiro, Michael D

2018-05-04

The domestic rock pigeon ( Columba livia ) is among the most widely distributed and phenotypically diverse avian species. C. livia is broadly studied in ecology, genetics, physiology, behavior, and evolutionary biology, and has recently emerged as a model for understanding the molecular basis of anatomical diversity, the magnetic sense, and other key aspects of avian biology. Here we report an update to the C. livia genome reference assembly and gene annotation dataset. Greatly increased scaffold lengths in the updated reference assembly, along with an updated annotation set, provide improved tools for evolutionary and functional genetic studies of the pigeon, and for comparative avian genomics in general. Copyright © 2018 Holt et al.

Functional Annotation of the Arabidopsis Genome Using Controlled Vocabularies1

PubMed Central

Berardini, Tanya Z.; Mundodi, Suparna; Reiser, Leonore; Huala, Eva; Garcia-Hernandez, Margarita; Zhang, Peifen; Mueller, Lukas A.; Yoon, Jungwoon; Doyle, Aisling; Lander, Gabriel; Moseyko, Nick; Yoo, Danny; Xu, Iris; Zoeckler, Brandon; Montoya, Mary; Miller, Neil; Weems, Dan; Rhee, Seung Y.

2004-01-01

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species. PMID:15173566

Re-annotation, improved large-scale assembly and establishment of a catalogue of noncoding loci for the genome of the model brown alga Ectocarpus.

PubMed

Cormier, Alexandre; Avia, Komlan; Sterck, Lieven; Derrien, Thomas; Wucher, Valentin; Andres, Gwendoline; Monsoor, Misharl; Godfroy, Olivier; Lipinska, Agnieszka; Perrineau, Marie-Mathilde; Van De Peer, Yves; Hitte, Christophe; Corre, Erwan; Coelho, Susana M; Cock, J Mark

2017-04-01

The genome of the filamentous brown alga Ectocarpus was the first to be completely sequenced from within the brown algal group and has served as a key reference genome both for this lineage and for the stramenopiles. We present a complete structural and functional reannotation of the Ectocarpus genome. The large-scale assembly of the Ectocarpus genome was significantly improved and genome-wide gene re-annotation using extensive RNA-seq data improved the structure of 11 108 existing protein-coding genes and added 2030 new loci. A genome-wide analysis of splicing isoforms identified an average of 1.6 transcripts per locus. A large number of previously undescribed noncoding genes were identified and annotated, including 717 loci that produce long noncoding RNAs. Conservation of lncRNAs between Ectocarpus and another brown alga, the kelp Saccharina japonica, suggests that at least a proportion of these loci serve a function. Finally, a large collection of single nucleotide polymorphism-based markers was developed for genetic analyses. These resources are available through an updated and improved genome database. This study significantly improves the utility of the Ectocarpus genome as a high-quality reference for the study of many important aspects of brown algal biology and as a reference for genomic analyses across the stramenopiles. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

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

PubMed Central

Oduru, Sreedhar; Campbell, Janee L; Karri, SriTulasi; Hendry, William J; Khan, Shafiq A; Williams, Simon C

2003-01-01

Background Complete genome annotation will likely be achieved through a combination of computer-based analysis of available genome sequences combined with direct experimental characterization of expressed regions of individual genomes. We have utilized a comparative genomics approach involving the sequencing of randomly selected hamster testis cDNAs to begin to identify genes not previously annotated on the human, mouse, rat and Fugu (pufferfish) genomes. Results 735 distinct sequences were analyzed for their relatedness to known sequences in public databases. Eight of these sequences were derived from previously unidentified genes and expression of these genes in testis was confirmed by Northern blotting. The genomic locations of each sequence were mapped in human, mouse, rat and pufferfish, where applicable, and the structure of their cognate genes was derived using computer-based predictions, genomic comparisons and analysis of uncharacterized cDNA sequences from human and macaque. Conclusion The use of a comparative genomics approach resulted in the identification of eight cDNAs that correspond to previously uncharacterized genes in the human genome. The proteins encoded by these genes included a new member of the kinesin superfamily, a SET/MYND-domain protein, and six proteins for which no specific function could be predicted. Each gene was expressed primarily in testis, suggesting that they may play roles in the development and/or function of testicular cells. PMID:12783626

Genome content analysis yields new insights into the relationship between the human malaria parasite Plasmodium falciparum and its anopheline vectors.

PubMed

Oppenheim, Sara J; Rosenfeld, Jeffrey A; DeSalle, Rob

2017-02-27

The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach.

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

PubMed

Lewis, Tony E; Sillitoe, Ian; Andreeva, Antonina; Blundell, Tom L; Buchan, Daniel W A; Chothia, Cyrus; Cuff, Alison; Dana, Jose M; Filippis, Ioannis; Gough, Julian; Hunter, Sarah; Jones, David T; Kelley, Lawrence A; Kleywegt, Gerard J; Minneci, Federico; Mitchell, Alex; Murzin, Alexey G; Ochoa-Montaño, Bernardo; Rackham, Owen J L; Smith, James; Sternberg, Michael J E; Velankar, Sameer; Yeats, Corin; Orengo, Christine

2013-01-01

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome

PubMed Central

2010-01-01

Background A goal of the Bovine Genome Database (BGD; http://BovineGenome.org) has been to support the Bovine Genome Sequencing and Analysis Consortium (BGSAC) in the annotation and analysis of the bovine genome. We were faced with several challenges, including the need to maintain consistent quality despite diversity in annotation expertise in the research community, the need to maintain consistent data formats, and the need to minimize the potential duplication of annotation effort. With new sequencing technologies allowing many more eukaryotic genomes to be sequenced, the demand for collaborative annotation is likely to increase. Here we present our approach, challenges and solutions facilitating a large distributed annotation project. Results and Discussion BGD has provided annotation tools that supported 147 members of the BGSAC in contributing 3,871 gene models over a fifteen-week period, and these annotations have been integrated into the bovine Official Gene Set. Our approach has been to provide an annotation system, which includes a BLAST site, multiple genome browsers, an annotation portal, and the Apollo Annotation Editor configured to connect directly to our Chado database. In addition to implementing and integrating components of the annotation system, we have performed computational analyses to create gene evidence tracks and a consensus gene set, which can be viewed on individual gene pages at BGD. Conclusions We have provided annotation tools that alleviate challenges associated with distributed annotation. Our system provides a consistent set of data to all annotators and eliminates the need for annotators to format data. Involving the bovine research community in genome annotation has allowed us to leverage expertise in various areas of bovine biology to provide biological insight into the genome sequence. PMID:21092105

High precision multi-genome scale reannotation of enzyme function by EFICAz

PubMed Central

Arakaki, Adrian K; Tian, Weidong; Skolnick, Jeffrey

2006-01-01

Background The functional annotation of most genes in newly sequenced genomes is inferred from similarity to previously characterized sequences, an annotation strategy that often leads to erroneous assignments. We have performed a reannotation of 245 genomes using an updated version of EFICAz, a highly precise method for enzyme function prediction. Results Based on our three-field EC number predictions, we have obtained lower-bound estimates for the average enzyme content in Archaea (29%), Bacteria (30%) and Eukarya (18%). Most annotations added in KEGG from 2005 to 2006 agree with EFICAz predictions made in 2005. The coverage of EFICAz predictions is significantly higher than that of KEGG, especially for eukaryotes. Thousands of our novel predictions correspond to hypothetical proteins. We have identified a subset of 64 hypothetical proteins with low sequence identity to EFICAz training enzymes, whose biochemical functions have been recently characterized and find that in 96% (84%) of the cases we correctly identified their three-field (four-field) EC numbers. For two of the 64 hypothetical proteins: PA1167 from Pseudomonas aeruginosa, an alginate lyase (EC 4.2.2.3) and Rv1700 of Mycobacterium tuberculosis H37Rv, an ADP-ribose diphosphatase (EC 3.6.1.13), we have detected annotation lag of more than two years in databases. Two examples are presented where EFICAz predictions act as hypothesis generators for understanding the functional roles of hypothetical proteins: FLJ11151, a human protein overexpressed in cancer that EFICAz identifies as an endopolyphosphatase (EC 3.6.1.10), and MW0119, a protein of Staphylococcus aureus strain MW2 that we propose as candidate virulence factor based on its EFICAz predicted activity, sphingomyelin phosphodiesterase (EC 3.1.4.12). Conclusion Our results suggest that we have generated enzyme function annotations of high precision and recall. These predictions can be mined and correlated with other information sources to generate biologically significant hypotheses and can be useful for comparative genome analysis and automated metabolic pathway reconstruction. PMID:17166279

PathFinder: reconstruction and dynamic visualization of metabolic pathways.

PubMed

Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert

2002-01-01

Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

Approaches to Fungal Genome Annotation

PubMed Central

Haas, Brian J.; Zeng, Qiandong; Pearson, Matthew D.; Cuomo, Christina A.; Wortman, Jennifer R.

2011-01-01

Fungal genome annotation is the starting point for analysis of genome content. This generally involves the application of diverse methods to identify features on a genome assembly such as protein-coding and non-coding genes, repeats and transposable elements, and pseudogenes. Here we describe tools and methods leveraged for eukaryotic genome annotation with a focus on the annotation of fungal nuclear and mitochondrial genomes. We highlight the application of the latest technologies and tools to improve the quality of predicted gene sets. The Broad Institute eukaryotic genome annotation pipeline is described as one example of how such methods and tools are integrated into a sequencing center’s production genome annotation environment. PMID:22059117

Dictionary-driven protein annotation

PubMed Central

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

2002-01-01

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/. PMID:12202776

Transcriptome Assembly, Gene Annotation and Tissue Gene Expression Atlas of the Rainbow Trout

PubMed Central

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. PMID:25793877

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship.

PubMed

Brunet, Marie A; Levesque, Sébastien A; Hunting, Darel J; Cohen, Alan A; Roucou, Xavier

2018-05-01

Technological advances promise unprecedented opportunities for whole exome sequencing and proteomic analyses of populations. Currently, data from genome and exome sequencing or proteomic studies are searched against reference genome annotations. This provides the foundation for research and clinical screening for genetic causes of pathologies. However, current genome annotations substantially underestimate the proteomic information encoded within a gene. Numerous studies have now demonstrated the expression and function of alternative (mainly small, sometimes overlapping) ORFs within mature gene transcripts. This has important consequences for the correlation of phenotypes and genotypes. Most alternative ORFs are not yet annotated because of a lack of evidence, and this absence from databases precludes their detection by standard proteomic methods, such as mass spectrometry. Here, we demonstrate how current approaches tend to overlook alternative ORFs, hindering the discovery of new genetic drivers and fundamental research. We discuss available tools and techniques to improve identification of proteins from alternative ORFs and finally suggest a novel annotation system to permit a more complete representation of the transcriptomic and proteomic information contained within a gene. Given the crucial challenge of distinguishing functional ORFs from random ones, the suggested pipeline emphasizes both experimental data and conservation signatures. The addition of alternative ORFs in databases will render identification less serendipitous and advance the pace of research and genomic knowledge. This review highlights the urgent medical and research need to incorporate alternative ORFs in current genome annotations and thus permit their inclusion in hypotheses and models, which relate phenotypes and genotypes. © 2018 Brunet et al.; Published by Cold Spring Harbor Laboratory Press.

Sequencing and comparative genomic analysis of 1227 Felis catus cDNA sequences enriched for developmental, clinical and nutritional phenotypes

PubMed Central

2012-01-01

Background The feline genome is valuable to the veterinary and model organism genomics communities because the cat is an obligate carnivore and a model for endangered felids. The initial public release of the Felis catus genome assembly provided a framework for investigating the genomic basis of feline biology. However, the entire set of protein coding genes has not been elucidated. Results We identified and characterized 1227 protein coding feline sequences, of which 913 map to public sequences and 314 are novel. These sequences have been deposited into NCBI's genbank database and complement public genomic resources by providing additional protein coding sequences that fill in some of the gaps in the feline genome assembly. Through functional and comparative genomic analyses, we gained an understanding of the role of these sequences in feline development, nutrition and health. Specifically, we identified 104 orthologs of human genes associated with Mendelian disorders. We detected negative selection within sequences with gene ontology annotations associated with intracellular trafficking, cytoskeleton and muscle functions. We detected relatively less negative selection on protein sequences encoding extracellular networks, apoptotic pathways and mitochondrial gene ontology annotations. Additionally, we characterized feline cDNA sequences that have mouse orthologs associated with clinical, nutritional and developmental phenotypes. Together, this analysis provides an overview of the value of our cDNA sequences and enhances our understanding of how the feline genome is similar to, and different from other mammalian genomes. Conclusions The cDNA sequences reported here expand existing feline genomic resources by providing high-quality sequences annotated with comparative genomic information providing functional, clinical, nutritional and orthologous gene information. PMID:22257742

SNPit: a federated data integration system for the purpose of functional SNP annotation.

PubMed

Shen, Terry H; Carlson, Christopher S; Tarczy-Hornoch, Peter

2009-08-01

Genome wide association studies can potentially identify the genetic causes behind the majority of human diseases. With the advent of more advanced genotyping techniques, there is now an explosion of data gathered on single nucleotide polymorphisms (SNPs). The need exists for an integrated system that can provide up-to-date functional annotation information on SNPs. We have developed the SNP Integration Tool (SNPit) system to address this need. Built upon a federated data integration system, SNPit provides current information on a comprehensive list of SNP data sources. Additional logical inference analysis was included through an inference engine plug in. The SNPit web servlet is available online for use. SNPit allows users to go to one source for up-to-date information on the functional annotation of SNPs. A tool that can help to integrate and analyze the potential functional significance of SNPs is important for understanding the results from genome wide association studies.

Dana-Farber Cancer Institute | Office of Cancer Genomics

Cancer.gov

Functional Annotation of Cancer Genomes Principal Investigator: William C. Hahn, M.D., Ph.D. The comprehensive characterization of cancer genomes has and will continue to provide an increasingly complete catalog of genetic alterations in specific cancers. However, most epithelial cancers harbor hundreds of genetic alterations as a consequence of genomic instability. Therefore, the functional consequences of the majority of mutations remain unclear.

Rice-Map: a new-generation rice genome browser.

PubMed

Wang, Jun; Kong, Lei; Zhao, Shuqi; Zhang, He; Tang, Liang; Li, Zhe; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2011-03-30

The concurrent release of rice genome sequences for two subspecies (Oryza sativa L. ssp. japonica and Oryza sativa L. ssp. indica) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively. More than one hundred annotation tracks (81 for japonica and 82 for indica) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria. Rice-Map delivers abundant up-to-date japonica and indica annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at http://www.ricemap.org/, with all data available for free downloading.

Characterization of "cis"-regulatory elements ("c"RE) associated with mammary gland function

USDA-ARS?s Scientific Manuscript database

The Bos taurus genome assembly has propelled dairy science into a new era; still, most of the information encoded in the genome has not yet been decoded. The human Encyclopedia of DNA Elements (ENCODE) project has spearheaded the identification and annotation of functional genomic elements in the hu...

Genome of the Asian longhorned beetle, Anoplophora glabripennis), a globally significant invasive species, reveals key functional and evolutionary innovations at the beetle-plant interface

USDA-ARS?s Scientific Manuscript database

The Asian longhorned beetle (Anoplophora glabripennis; AGLAB) is a globally significant invasive species capable of inflicting severe feeding damage on many important orchard, ornamental and forest trees. Genome sequencing, annotation, gene expression assays, and functional and comparative genomic s...

Genome re-annotation of the wild strawberry Fragaria vesca using extensive Illumina- and SMRT-based RNA-seq datasets

PubMed Central

Li, Yongping; Wei, Wei; Feng, Jia; Luo, Huifeng; Pi, Mengting; Liu, Zhongchi; Kang, Chunying

2018-01-01

Abstract The genome of the wild diploid strawberry species Fragaria vesca, an ideal model system of cultivated strawberry (Fragaria × ananassa, octoploid) and other Rosaceae family crops, was first published in 2011 and followed by a new assembly (Fvb). However, the annotation for Fvb mainly relied on ab initio predictions and included only predicted coding sequences, therefore an improved annotation is highly desirable. Here, a new annotation version named v2.0.a2 was created for the Fvb genome by a pipeline utilizing one PacBio library, 90 Illumina RNA-seq libraries, and 9 small RNA-seq libraries. Altogether, 18,641 genes (55.6% out of 33,538 genes) were augmented with information on the 5′ and/or 3′ UTRs, 13,168 (39.3%) protein-coding genes were modified or newly identified, and 7,370 genes were found to possess alternative isoforms. In addition, 1,938 long non-coding RNAs, 171 miRNAs, and 51,714 small RNA clusters were integrated into the annotation. This new annotation of F. vesca is substantially improved in both accuracy and integrity of gene predictions, beneficial to the gene functional studies in strawberry and to the comparative genomic analysis of other horticultural crops in Rosaceae family. PMID:29036429

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

Toward an Upgraded Honey Bee (Apis mellifera L.) Genome Annotation Using Proteogenomics.

PubMed

McAfee, Alison; Harpur, Brock A; Michaud, Sarah; Beavis, Ronald C; Kent, Clement F; Zayed, Amro; Foster, Leonard J

2016-02-05

The honey bee is a key pollinator in agricultural operations as well as a model organism for studying the genetics and evolution of social behavior. The Apis mellifera genome has been sequenced and annotated twice over, enabling proteomics and functional genomics methods for probing relevant aspects of their biology. One troubling trend that emerged from proteomic analyses is that honey bee peptide samples consistently result in lower peptide identification rates compared with other organisms. This suggests that the genome annotation can be improved, or atypical biological processes are interfering with the mass spectrometry workflow. First, we tested whether high levels of polymorphisms could explain some of the missed identifications by searching spectra against the reference proteome (OGSv3.2) versus a customized proteome of a single honey bee, but our results indicate that this contribution was minor. Likewise, error-tolerant peptide searches lead us to eliminate unexpected post-translational modifications as a major factor in missed identifications. We then used a proteogenomic approach with ~1500 raw files to search for missing genes and new exons, to revive discarded annotations and to identify over 2000 new coding regions. These results will contribute to a more comprehensive genome annotation and facilitate continued research on this important insect.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian

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

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

DOE PAGES

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian; ...

2017-03-06

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

Global Identification and Characterization of Transcriptionally Active Regions in the Rice Genome

PubMed Central

Stolc, Viktor; Deng, Wei; He, Hang; Korbel, Jan; Chen, Xuewei; Tongprasit, Waraporn; Ronald, Pamela; Chen, Runsheng; Gerstein, Mark; Wang Deng, Xing

2007-01-01

Genome tiling microarray studies have consistently documented rich transcriptional activity beyond the annotated genes. However, systematic characterization and transcriptional profiling of the putative novel transcripts on the genome scale are still lacking. We report here the identification of 25,352 and 27,744 transcriptionally active regions (TARs) not encoded by annotated exons in the rice (Oryza. sativa) subspecies japonica and indica, respectively. The non-exonic TARs account for approximately two thirds of the total TARs detected by tiling arrays and represent transcripts likely conserved between japonica and indica. Transcription of 21,018 (83%) japonica non-exonic TARs was verified through expression profiling in 10 tissue types using a re-array in which annotated genes and TARs were each represented by five independent probes. Subsequent analyses indicate that about 80% of the japonica TARs that were not assigned to annotated exons can be assigned to various putatively functional or structural elements of the rice genome, including splice variants, uncharacterized portions of incompletely annotated genes, antisense transcripts, duplicated gene fragments, and potential non-coding RNAs. These results provide a systematic characterization of non-exonic transcripts in rice and thus expand the current view of the complexity and dynamics of the rice transcriptome. PMID:17372628

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.

GenColors: annotation and comparative genomics of prokaryotes made easy.

PubMed

Romualdi, Alessandro; Felder, Marius; Rose, Dominic; Gausmann, Ulrike; Schilhabel, Markus; Glöckner, Gernot; Platzer, Matthias; Sühnel, Jürgen

2007-01-01

GenColors (gencolors.fli-leibniz.de) is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. A variety of export/import filters manages an effective data flow from sequence assembly and manipulation programs (e.g., GAP4) to GenColors and back as well as to standard GenBank file(s). The genome comparison tools include best bidirectional hits, gene conservation, syntenies, and gene core sets. Precomputed UniProt matches allow annotation and analysis in an effective manner. In addition to these analysis options, base-specific quality data (coverage and confidence) can also be handled if available. The GenColors system can be used both for annotation purposes in ongoing genome projects and as an analysis tool for finished genomes. GenColors comes in two types, as dedicated genome browsers and as the Jena Prokaryotic Genome Viewer (JPGV). Dedicated genome browsers contain genomic information on a set of related genomes and offer a large number of options for genome comparison. The system has been efficiently used in the genomic sequencing of Borrelia garinii and is currently applied to various ongoing genome projects on Borrelia, Legionella, Escherichia, and Pseudomonas genomes. One of these dedicated browsers, the Spirochetes Genome Browser (sgb.fli-leibniz.de) with Borrelia, Leptospira, and Treponema genomes, is freely accessible. The others will be released after finalization of the corresponding genome projects. JPGV (jpgv.fli-leibniz.de) offers information on almost all finished bacterial genomes, as compared to the dedicated browsers with reduced genome comparison functionality, however. As of January 2006, this viewer includes 632 genomic elements (e.g., chromosomes and plasmids) of 293 species. The system provides versatile quick and advanced search options for all currently known prokaryotic genomes and generates circular and linear genome plots. Gene information sheets contain basic gene information, database search options, and links to external databases. GenColors is also available on request for local installation.

Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics.

PubMed

Sakai, Hiroaki; Lee, Sung Shin; Tanaka, Tsuyoshi; Numa, Hisataka; Kim, Jungsok; Kawahara, Yoshihiro; Wakimoto, Hironobu; Yang, Ching-chia; Iwamoto, Masao; Abe, Takashi; Yamada, Yuko; Muto, Akira; Inokuchi, Hachiro; Ikemura, Toshimichi; Matsumoto, Takashi; Sasaki, Takuji; Itoh, Takeshi

2013-02-01

The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics.

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics.

PubMed

Omasits, Ulrich; Varadarajan, Adithi R; Schmid, Michael; Goetze, Sandra; Melidis, Damianos; Bourqui, Marc; Nikolayeva, Olga; Québatte, Maxime; Patrignani, Andrea; Dehio, Christoph; Frey, Juerg E; Robinson, Mark D; Wollscheid, Bernd; Ahrens, Christian H

2017-12-01

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae , Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote. © 2017 Omasits et al.; Published by Cold Spring Harbor Laboratory Press.

Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission.

PubMed

Geib, Scott M; Hall, Brian; Derego, Theodore; Bremer, Forest T; Cannoles, Kyle; Sim, Sheina B

2018-04-01

One of the most overlooked, yet critical, components of a whole genome sequencing (WGS) project is the submission and curation of the data to a genomic repository, most commonly the National Center for Biotechnology Information (NCBI). While large genome centers or genome groups have developed software tools for post-annotation assembly filtering, annotation, and conversion into the NCBI's annotation table format, these tools typically require back-end setup and connection to an Structured Query Language (SQL) database and/or some knowledge of programming (Perl, Python) to implement. With WGS becoming commonplace, genome sequencing projects are moving away from the genome centers and into the ecology or biology lab, where fewer resources are present to support the process of genome assembly curation. To fill this gap, we developed software to assess, filter, and transfer annotation and convert a draft genome assembly and annotation set into the NCBI annotation table (.tbl) format, facilitating submission to the NCBI Genome Assembly database. This software has no dependencies, is compatible across platforms, and utilizes a simple command to perform a variety of simple and complex post-analysis, pre-NCBI submission WGS project tasks. The Genome Annotation Generator is a consistent and user-friendly bioinformatics tool that can be used to generate a .tbl file that is consistent with the NCBI submission pipeline. The Genome Annotation Generator achieves the goal of providing a publicly available tool that will facilitate the submission of annotated genome assemblies to the NCBI. It is useful for any individual researcher or research group that wishes to submit a genome assembly of their study system to the NCBI.

Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission

PubMed Central

Hall, Brian; Derego, Theodore; Bremer, Forest T; Cannoles, Kyle

2018-01-01

Abstract Background One of the most overlooked, yet critical, components of a whole genome sequencing (WGS) project is the submission and curation of the data to a genomic repository, most commonly the National Center for Biotechnology Information (NCBI). While large genome centers or genome groups have developed software tools for post-annotation assembly filtering, annotation, and conversion into the NCBI’s annotation table format, these tools typically require back-end setup and connection to an Structured Query Language (SQL) database and/or some knowledge of programming (Perl, Python) to implement. With WGS becoming commonplace, genome sequencing projects are moving away from the genome centers and into the ecology or biology lab, where fewer resources are present to support the process of genome assembly curation. To fill this gap, we developed software to assess, filter, and transfer annotation and convert a draft genome assembly and annotation set into the NCBI annotation table (.tbl) format, facilitating submission to the NCBI Genome Assembly database. This software has no dependencies, is compatible across platforms, and utilizes a simple command to perform a variety of simple and complex post-analysis, pre-NCBI submission WGS project tasks. Findings The Genome Annotation Generator is a consistent and user-friendly bioinformatics tool that can be used to generate a .tbl file that is consistent with the NCBI submission pipeline Conclusions The Genome Annotation Generator achieves the goal of providing a publicly available tool that will facilitate the submission of annotated genome assemblies to the NCBI. It is useful for any individual researcher or research group that wishes to submit a genome assembly of their study system to the NCBI. PMID:29635297

The cacao Criollo genome v2.0: an improved version of the genome for genetic and functional genomic studies.

PubMed

Argout, X; Martin, G; Droc, G; Fouet, O; Labadie, K; Rivals, E; Aury, J M; Lanaud, C

2017-09-15

Theobroma cacao L., native to the Amazonian basin of South America, is an economically important fruit tree crop for tropical countries as a source of chocolate. The first draft genome of the species, from a Criollo cultivar, was published in 2011. Although a useful resource, some improvements are possible, including identifying misassemblies, reducing the number of scaffolds and gaps, and anchoring un-anchored sequences to the 10 chromosomes. We used a NGS-based approach to significantly improve the assembly of the Belizian Criollo B97-61/B2 genome. We combined four Illumina large insert size mate paired libraries with 52x of Pacific Biosciences long reads to correct misassembled regions and reduced the number of scaffolds. We then used genotyping by sequencing (GBS) methods to increase the proportion of the assembly anchored to chromosomes. The scaffold number decreased from 4,792 in assembly V1 to 554 in V2 while the scaffold N50 size has increased from 0.47 Mb in V1 to 6.5 Mb in V2. A total of 96.7% of the assembly was anchored to the 10 chromosomes compared to 66.8% in the previous version. Unknown sites (Ns) were reduced from 10.8% to 5.7%. In addition, we updated the functional annotations and performed a new RefSeq structural annotation based on RNAseq evidence. Theobroma cacao Criollo genome version 2 will be a valuable resource for the investigation of complex traits at the genomic level and for future comparative genomics and genetics studies in cacao tree. New functional tools and annotations are available on the Cocoa Genome Hub ( http://cocoa-genome-hub.southgreen.fr ).

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

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

PubMed

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.

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

PubMed

Dhanyalakshmi, K H; Naika, Mahantesha B N; Sajeevan, R S; Mathew, Oommen K; Shafi, K Mohamed; Sowdhamini, Ramanathan; N Nataraja, Karaba

2016-01-01

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

MEGAnnotator: a user-friendly pipeline for microbial genomes assembly and annotation.

PubMed

Lugli, Gabriele Andrea; Milani, Christian; Mancabelli, Leonardo; van Sinderen, Douwe; Ventura, Marco

2016-04-01

Genome annotation is one of the key actions that must be undertaken in order to decipher the genetic blueprint of organisms. Thus, a correct and reliable annotation is essential in rendering genomic data valuable. Here, we describe a bioinformatics pipeline based on freely available software programs coordinated by a multithreaded script named MEGAnnotator (Multithreaded Enhanced prokaryotic Genome Annotator). This pipeline allows the generation of multiple annotated formats fulfilling the NCBI guidelines for assembled microbial genome submission, based on DNA shotgun sequencing reads, and minimizes manual intervention, while also reducing waiting times between software program executions and improving final quality of both assembly and annotation outputs. MEGAnnotator provides an efficient way to pre-arrange the assembly and annotation work required to process NGS genome sequence data. The script improves the final quality of microbial genome annotation by reducing ambiguous annotations. Moreover, the MEGAnnotator platform allows the user to perform a partial annotation of pre-assembled genomes and includes an option to accomplish metagenomic data set assemblies. MEGAnnotator platform will be useful for microbiologists interested in genome analyses of bacteria as well as those investigating the complexity of microbial communities that do not possess the necessary skills to prepare their own bioinformatics pipeline. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Improved maize reference genome with single-molecule technologies.

PubMed

Jiao, Yinping; Peluso, Paul; Shi, Jinghua; Liang, Tiffany; Stitzer, Michelle C; Wang, Bo; Campbell, Michael S; Stein, Joshua C; Wei, Xuehong; Chin, Chen-Shan; Guill, Katherine; Regulski, Michael; Kumari, Sunita; Olson, Andrew; Gent, Jonathan; Schneider, Kevin L; Wolfgruber, Thomas K; May, Michael R; Springer, Nathan M; Antoniou, Eric; McCombie, W Richard; Presting, Gernot G; McMullen, Michael; Ross-Ibarra, Jeffrey; Dawe, R Kelly; Hastie, Alex; Rank, David R; Ware, Doreen

2017-06-22

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here we report the assembly and annotation of a reference genome of maize, a genetic and agricultural model species, using single-molecule real-time sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and notable improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed more than 130,000 intact transposable elements, allowing us to identify transposable element lineage expansions that are unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by single-molecule real-time sequencing. In addition, comparative optical mapping of two other inbred maize lines revealed a prevalence of deletions in regions of low gene density and maize lineage-specific genes.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

Development of FuGO: An Ontology for Functional Genomics Investigations

PubMed Central

Whetzel, Patricia L.; Brinkman, Ryan R.; Causton, Helen C.; Fan, Liju; Field, Dawn; Fostel, Jennifer; Fragoso, Gilberto; Gray, Tanya; Heiskanen, Mervi; Hernandez-Boussard, Tina; Morrison, Norman; Parkinson, Helen; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Schober, Daniel; Smith, Barry; Stevens, Robert; Stoeckert, Christian J.; Taylor, Chris; White, Joe; Wood, Andrew

2009-01-01

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the “semantic glue” to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans. PMID:16901226

Genome-wide annotation of the soybean WRKY family and functional characterization of genes involved in response to Phakopsora pachyrhizi infection.

PubMed

Bencke-Malato, Marta; Cabreira, Caroline; Wiebke-Strohm, Beatriz; Bücker-Neto, Lauro; Mancini, Estefania; Osorio, Marina B; Homrich, Milena S; Turchetto-Zolet, Andreia Carina; De Carvalho, Mayra C C G; Stolf, Renata; Weber, Ricardo L M; Westergaard, Gastón; Castagnaro, Atílio P; Abdelnoor, Ricardo V; Marcelino-Guimarães, Francismar C; Margis-Pinheiro, Márcia; Bodanese-Zanettini, Maria Helena

2014-09-10

Many previous studies have shown that soybean WRKY transcription factors are involved in the plant response to biotic and abiotic stresses. Phakopsora pachyrhizi is the causal agent of Asian Soybean Rust, one of the most important soybean diseases. There are evidences that WRKYs are involved in the resistance of some soybean genotypes against that fungus. The number of WRKY genes already annotated in soybean genome was underrepresented. In the present study, a genome-wide annotation of the soybean WRKY family was carried out and members involved in the response to P. pachyrhizi were identified. As a result of a soybean genomic databases search, 182 WRKY-encoding genes were annotated and 33 putative pseudogenes identified. Genes involved in the response to P. pachyrhizi infection were identified using superSAGE, RNA-Seq of microdissected lesions and microarray experiments. Seventy-five genes were differentially expressed during fungal infection. The expression of eight WRKY genes was validated by RT-qPCR. The expression of these genes in a resistant genotype was earlier and/or stronger compared with a susceptible genotype in response to P. pachyrhizi infection. Soybean somatic embryos were transformed in order to overexpress or silence WRKY genes. Embryos overexpressing a WRKY gene were obtained, but they were unable to convert into plants. When infected with P. pachyrhizi, the leaves of the silenced transgenic line showed a higher number of lesions than the wild-type plants. The present study reports a genome-wide annotation of soybean WRKY family. The participation of some members in response to P. pachyrhizi infection was demonstrated. The results contribute to the elucidation of gene function and suggest the manipulation of WRKYs as a strategy to increase fungal resistance in soybean plants.

Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

PubMed

Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

1997-01-01

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.

The American cranberry mitochondrial genome reveals the presence of selenocysteine (tRNA-Sec and SECIS) insertion machinery in land plants.

PubMed

Fajardo, Diego; Schlautman, Brandon; Steffan, Shawn; Polashock, James; Vorsa, Nicholi; Zalapa, Juan

2014-02-25

This is the first de novo assembly and annotation of a complete mitochondrial genome in the Ericales order from the American cranberry (Vaccinium macrocarpon Ait.). Moreover, only four complete Asterid mitochondrial genomes have been made publicly available. The cranberry mitochondrial genome was assembled and reconstructed from whole genome 454 Roche GS-FLX and Illumina shotgun sequences. Compared with other Asterids, the reconstruction of the genome revealed an average size mitochondrion (459,678 nt) with relatively little repetitive sequences and DNA of plastid origin. The complete mitochondrial genome of cranberry was annotated obtaining a total of 34 genes classified based on their putative function, plus three ribosomal RNAs, and 17 transfer RNAs. Maternal organellar cranberry inheritance was inferred by analyzing gene variation in the cranberry mitochondria and plastid genomes. The annotation of cranberry mitochondrial genome revealed the presence of two copies of tRNA-Sec and a selenocysteine insertion sequence (SECIS) element which were lost in plants during evolution. This is the first report of a land plant possessing selenocysteine insertion machinery at the sequence level. Published by Elsevier B.V.

Efficient Integrative Multi-SNP Association Analysis via Deterministic Approximation of Posteriors.

PubMed

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

2016-06-02

With the increasing availability of functional genomic data, incorporating genomic annotations into genetic association analysis has become a standard procedure. However, the existing methods often lack rigor and/or computational efficiency and consequently do not maximize the utility of functional annotations. In this paper, we propose a rigorous inference procedure to perform integrative association analysis incorporating genomic annotations for both traditional GWASs and emerging molecular QTL mapping studies. In particular, we propose an algorithm, named deterministic approximation of posteriors (DAP), which enables highly efficient and accurate joint enrichment analysis and identification of multiple causal variants. We use a series of simulation studies to highlight the power and computational efficiency of our proposed approach and further demonstrate it by analyzing the cross-population eQTL data from the GEUVADIS project and the multi-tissue eQTL data from the GTEx project. In particular, we find that genetic variants predicted to disrupt transcription factor binding sites are enriched in cis-eQTLs across all tissues. Moreover, the enrichment estimates obtained across the tissues are correlated with the cell types for which the annotations are derived. Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Elucidation of primary metabolic pathways in Aspergillus species: orphaned research in characterizing orphan genes.

PubMed

Andersen, Mikael Rørdam

2014-11-01

Primary metabolism affects all phenotypical traits of filamentous fungi. Particular examples include reacting to extracellular stimuli, producing precursor molecules required for cell division and morphological changes as well as providing monomer building blocks for production of secondary metabolites and extracellular enzymes. In this review, all annotated genes from four Aspergillus species have been examined. In this process, it becomes evident that 80-96% of the genes (depending on the species) are still without verified function. A significant proportion of the genes with verified metabolic functions are assigned to secondary or extracellular metabolism, leaving only 2-4% of the annotated genes within primary metabolism. It is clear that primary metabolism has not received the same attention in the post-genomic area as many other research areas--despite its role at the very centre of cellular function. However, several methods can be employed to use the metabolic networks in tandem with comparative genomics to accelerate functional assignment of genes in primary metabolism. In particular, gaps in metabolic pathways can be used to assign functions to orphan genes. In this review, applications of this from the Aspergillus genes will be examined, and it is proposed that, where feasible, this should be a standard part of functional annotation of fungal genomes. © The Author 2014. Published by Oxford University Press.

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 to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface.« less

Likelihood-Based Gene Annotations for Gap Filling and Quality Assessment in Genome-Scale Metabolic Models

PubMed Central

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

2014-01-01

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 obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface. PMID:25329157

Assembling the Setaria italica L. Beauv. genome into nine chromosomes and insights into regions affecting growth and drought tolerance

PubMed Central

Tsai, Kevin J.; Lu, Mei-Yeh Jade; Yang, Kai-Jung; Li, Mengyun; Teng, Yuchuan; Chen, Shihmay; Ku, Maurice S. B.; Li, Wen-Hsiung

2016-01-01

The diploid C4 plant foxtail millet (Setaria italica L. Beauv.) is an important crop in many parts of Africa and Asia for the vast consumption of its grain and ability to grow in harsh environments, but remains understudied in terms of complete genomic architecture. To date, there have been only two genome assembly and annotation efforts with neither assembly reaching over 86% of the estimated genome size. We have combined de novo assembly with custom reference-guided improvements on a popular cultivar of foxtail millet and have achieved a genome assembly of 477 Mbp in length, which represents over 97% of the estimated 490 Mbp. The assembly anchors over 98% of the predicted genes to the nine assembled nuclear chromosomes and contains more functional annotation gene models than previous assemblies. Our annotation has identified a large number of unique gene ontology terms related to metabolic activities, a region of chromosome 9 with several growth factor proteins, and regions syntenic with pearl millet or maize genomic regions that have been previously shown to affect growth. The new assembly and annotation for this important species can be used for detailed investigation and future innovations in growth for millet and other grains. PMID:27734962

Assembling the Setaria italica L. Beauv. genome into nine chromosomes and insights into regions affecting growth and drought tolerance.

PubMed

Tsai, Kevin J; Lu, Mei-Yeh Jade; Yang, Kai-Jung; Li, Mengyun; Teng, Yuchuan; Chen, Shihmay; Ku, Maurice S B; Li, Wen-Hsiung

2016-10-13

The diploid C 4 plant foxtail millet (Setaria italica L. Beauv.) is an important crop in many parts of Africa and Asia for the vast consumption of its grain and ability to grow in harsh environments, but remains understudied in terms of complete genomic architecture. To date, there have been only two genome assembly and annotation efforts with neither assembly reaching over 86% of the estimated genome size. We have combined de novo assembly with custom reference-guided improvements on a popular cultivar of foxtail millet and have achieved a genome assembly of 477 Mbp in length, which represents over 97% of the estimated 490 Mbp. The assembly anchors over 98% of the predicted genes to the nine assembled nuclear chromosomes and contains more functional annotation gene models than previous assemblies. Our annotation has identified a large number of unique gene ontology terms related to metabolic activities, a region of chromosome 9 with several growth factor proteins, and regions syntenic with pearl millet or maize genomic regions that have been previously shown to affect growth. The new assembly and annotation for this important species can be used for detailed investigation and future innovations in growth for millet and other grains.

Improved annotation of the insect vector of citrus greening disease: biocuration by a diverse genomics community

PubMed Central

Hosmani, Prashant S.; Villalobos-Ayala, Krystal; Miller, Sherry; Shippy, Teresa; Flores, Mirella; Rosendale, Andrew; Cordola, Chris; Bell, Tracey; Mann, Hannah; DeAvila, Gabe; DeAvila, Daniel; Moore, Zachary; Buller, Kyle; Ciolkevich, Kathryn; Nandyal, Samantha; Mahoney, Robert; Van Voorhis, Joshua; Dunlevy, Megan; Farrow, David; Hunter, David; Morgan, Taylar; Shore, Kayla; Guzman, Victoria; Izsak, Allison; Dixon, Danielle E.; Cridge, Andrew; Cano, Liliana; Cao, Xiaolong; Jiang, Haobo; Leng, Nan; Johnson, Shannon; Cantarel, Brandi L.; Richards, Stephen; English, Adam; Shatters, Robert G.; Childers, Chris; Chen, Mei-Ju; Hunter, Wayne; Cilia, Michelle; Mueller, Lukas A.; Munoz-Torres, Monica; Nelson, David; Poelchau, Monica F.; Benoit, Joshua B.; Wiersma-Koch, Helen; D’Elia, Tom; Brown, Susan J.

2017-01-01

Abstract The Asian citrus psyllid (Diaphorina citri Kuwayama) is the insect vector of the bacterium Candidatus Liberibacter asiaticus (CLas), the pathogen associated with citrus Huanglongbing (HLB, citrus greening). HLB threatens citrus production worldwide. Suppression or reduction of the insect vector using chemical insecticides has been the primary method to inhibit the spread of citrus greening disease. Accurate structural and functional annotation of the Asian citrus psyllid genome, as well as a clear understanding of the interactions between the insect and CLas, are required for development of new molecular-based HLB control methods. A draft assembly of the D. citri genome has been generated and annotated with automated pipelines. However, knowledge transfer from well-curated reference genomes such as that of Drosophila melanogaster to newly sequenced ones is challenging due to the complexity and diversity of insect genomes. To identify and improve gene models as potential targets for pest control, we manually curated several gene families with a focus on genes that have key functional roles in D. citri biology and CLas interactions. This community effort produced 530 manually curated gene models across developmental, physiological, RNAi regulatory and immunity-related pathways. As previously shown in the pea aphid, RNAi machinery genes putatively involved in the microRNA pathway have been specifically duplicated. A comprehensive transcriptome enabled us to identify a number of gene families that are either missing or misassembled in the draft genome. In order to develop biocuration as a training experience, we included undergraduate and graduate students from multiple institutions, as well as experienced annotators from the insect genomics research community. The resulting gene set (OGS v1.0) combines both automatically predicted and manually curated gene models. Database URL: https://citrusgreening.org/ PMID:29220441

The future of transposable element annotation and their classification in the light of functional genomics - what we can learn from the fables of Jean de la Fontaine?

PubMed

Arensburger, Peter; Piégu, Benoît; Bigot, Yves

2016-01-01

Transposable element (TE) science has been significantly influenced by the pioneering ideas of David Finnegan near the end of the last century, as well as by the classification systems that were subsequently developed. Today, whole genome TE annotation is mostly done using tools that were developed to aid gene annotation rather than to specifically study TEs. We argue that further progress in the TE field is impeded both by current TE classification schemes and by a failure to recognize that TE biology is fundamentally different from that of multicellular organisms. Novel genome wide TE annotation methods are helping to redefine our understanding of TE sequence origins and evolution. We briefly discuss some of these new methods as well as ideas for possible alternative classification schemes. Our hope is to encourage the formation of a society to organize a larger debate on these questions and to promote the adoption of standards for annotation and an improved TE classification.

Revised annotation of Plutella xylostella microRNAs and their genome-wide target identification.

PubMed

Etebari, K; Asgari, S

2016-12-01

The diamondback moth, Plutella xylostella, is the most devastating pest of brassica crops worldwide. Although 128 mature microRNAs (miRNAs) have been annotated from this species in miRBase, there is a need to extend and correct the current P. xylostella miRNA repertoire as a result of its recently improved genome assembly and more available small RNA sequence data. We used our new ultra-deep sequence data and bioinformatics to re-annotate the P. xylostella genome for high confidence miRNAs with the correct 5p and 3p arm features. Furthermore, all the P. xylostella annotated genes were also screened to identify potential miRNA binding sites using three target-predicting algorithms. In total, 203 mature miRNAs were annotated, including 33 novel miRNAs. We identified 7691 highly confident binding sites for 160 pxy-miRNAs. The data provided here will facilitate future studies involving functional analyses of P. xylostella miRNAs as a platform to introduce novel approaches for sustainable management of this destructive pest. © 2016 The Royal Entomological Society.

Apollo: a sequence annotation editor

PubMed Central

Lewis, SE; Searle, SMJ; Harris, N; Gibson, M; Iyer, V; Richter, J; Wiel, C; Bayraktaroglu, L; Birney, E; Crosby, MA; Kaminker, JS; Matthews, BB; Prochnik, SE; Smith, CD; Tupy, JL; Rubin, GM; Misra, S; Mungall, CJ; Clamp, ME

2002-01-01

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects. PMID:12537571

Evidence-Based Annotation of Gene Function in Shewanella oneidensis MR-1 Using Genome-Wide Fitness Profiling across 121 Conditions

PubMed Central

Deutschbauer, Adam; Price, Morgan N.; Wetmore, Kelly M.; Shao, Wenjun; Baumohl, Jason K.; Xu, Zhuchen; Nguyen, Michelle; Tamse, Raquel; Davis, Ronald W.; Arkin, Adam P.

2011-01-01

Most genes in bacteria are experimentally uncharacterized and cannot be annotated with a specific function. Given the great diversity of bacteria and the ease of genome sequencing, high-throughput approaches to identify gene function experimentally are needed. Here, we use pools of tagged transposon mutants in the metal-reducing bacterium Shewanella oneidensis MR-1 to probe the mutant fitness of 3,355 genes in 121 diverse conditions including different growth substrates, alternative electron acceptors, stresses, and motility. We find that 2,350 genes have a pattern of fitness that is significantly different from random and 1,230 of these genes (37% of our total assayed genes) have enough signal to show strong biological correlations. We find that genes in all functional categories have phenotypes, including hundreds of hypotheticals, and that potentially redundant genes (over 50% amino acid identity to another gene in the genome) are also likely to have distinct phenotypes. Using fitness patterns, we were able to propose specific molecular functions for 40 genes or operons that lacked specific annotations or had incomplete annotations. In one example, we demonstrate that the previously hypothetical gene SO_3749 encodes a functional acetylornithine deacetylase, thus filling a missing step in S. oneidensis metabolism. Additionally, we demonstrate that the orphan histidine kinase SO_2742 and orphan response regulator SO_2648 form a signal transduction pathway that activates expression of acetyl-CoA synthase and is required for S. oneidensis to grow on acetate as a carbon source. Lastly, we demonstrate that gene expression and mutant fitness are poorly correlated and that mutant fitness generates more confident predictions of gene function than does gene expression. The approach described here can be applied generally to create large-scale gene-phenotype maps for evidence-based annotation of gene function in prokaryotes. PMID:22125499

Proteins of Unknown Biochemical Function: A Persistent Problem and a Roadmap to Help Overcome It.

PubMed

Niehaus, Thomas D; Thamm, Antje M K; de Crécy-Lagard, Valérie; Hanson, Andrew D

2015-11-01

The number of sequenced genomes is rapidly increasing, but functional annotation of the genes in these genomes lags far behind. Even in Arabidopsis (Arabidopsis thaliana), only approximately 40% of enzyme- and transporter-encoding genes have credible functional annotations, and this number is even lower in nonmodel plants. Functional characterization of unknown genes is a challenge, but various databases (e.g. for protein localization and coexpression) can be mined to provide clues. If homologous microbial genes exist-and about one-half the genes encoding unknown enzymes and transporters in Arabidopsis have microbial homologs-cross-kingdom comparative genomics can powerfully complement plant-based data. Multiple lines of evidence can strengthen predictions and warrant experimental characterization. In some cases, relatively quick tests in genetically tractable microbes can determine whether a prediction merits biochemical validation, which is costly and demands specialized skills. © 2015 American Society of Plant Biologists. All Rights Reserved.

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

PubMed Central

Weiss, Andy; Broach, William H.; Wiemels, Richard E.; Mogen, Austin B.; Rice, Kelly C.

2016-01-01

ABSTRACT In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions. PMID:26861020

A comprehensive collection of annotations to interpret sequence variation in human mitochondrial transfer RNAs.

PubMed

Diroma, Maria Angela; Lubisco, Paolo; Attimonelli, Marcella

2016-11-08

The abundance of biological data characterizing the genomics era is contributing to a comprehensive understanding of human mitochondrial genetics. Nevertheless, many aspects are still unclear, specifically about the variability of the 22 human mitochondrial transfer RNA (tRNA) genes and their involvement in diseases. The complex enrichment and isolation of tRNAs in vitro leads to an incomplete knowledge of their post-transcriptional modifications and three-dimensional folding, essential for correct tRNA functioning. An accurate annotation of mitochondrial tRNA variants would be definitely useful and appreciated by mitochondrial researchers and clinicians since the most of bioinformatics tools for variant annotation and prioritization available so far cannot shed light on the functional role of tRNA variations. To this aim, we updated our MToolBox pipeline for mitochondrial DNA analysis of high throughput and Sanger sequencing data by integrating tRNA variant annotations in order to identify and characterize relevant variants not only in protein coding regions, but also in tRNA genes. The annotation step in the pipeline now provides detailed information for variants mapping onto the 22 mitochondrial tRNAs. For each mt-tRNA position along the entire genome, the relative tRNA numbering, tRNA type, cloverleaf secondary domains (loops and stems), mature nucleotide and interactions in the three-dimensional folding were reported. Moreover, pathogenicity predictions for tRNA and rRNA variants were retrieved from the literature and integrated within the annotations provided by MToolBox, both in the stand-alone version and web-based tool at the Mitochondrial Disease Sequence Data Resource (MSeqDR) website. All the information available in the annotation step of MToolBox were exploited to generate custom tracks which can be displayed in the GBrowse instance at MSeqDR website. To the best of our knowledge, specific data regarding mitochondrial variants in tRNA genes were introduced for the first time in a tool for mitochondrial genome analysis, supporting the interpretation of genetic variants in specific genomic contexts.

Using the underlying biological organization of the Mycobacterium tuberculosis functional network for protein function prediction.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2012-07-01

Despite ever-increasing amounts of sequence and functional genomics data, there is still a deficiency of functional annotation for many newly sequenced proteins. For Mycobacterium tuberculosis (MTB), more than half of its genome is still uncharacterized, which hampers the search for new drug targets within the bacterial pathogen and limits our understanding of its pathogenicity. As for many other genomes, the annotations of proteins in the MTB proteome were generally inferred from sequence homology, which is effective but its applicability has limitations. We have carried out large-scale biological data integration to produce an MTB protein functional interaction network. Protein functional relationships were extracted from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and additional functional interactions from microarray, sequence and protein signature data. The confidence level of protein relationships in the additional functional interaction data was evaluated using a dynamic data-driven scoring system. This functional network has been used to predict functions of uncharacterized proteins using Gene Ontology (GO) terms, and the semantic similarity between these terms measured using a state-of-the-art GO similarity metric. To achieve better trade-off between improvement of quality, genomic coverage and scalability, this prediction is done by observing the key principles driving the biological organization of the functional network. This study yields a new functionally characterized MTB strain CDC1551 proteome, consisting of 3804 and 3698 proteins out of 4195 with annotations in terms of the biological process and molecular function ontologies, respectively. These data can contribute to research into the Development of effective anti-tubercular drugs with novel biological mechanisms of action. Copyright © 2011 Elsevier B.V. All rights reserved.

University of Texas MD Anderson Cancer Center (UT-MDACC): Systematic Functional Annotation of Somatic Mutations in Cancer | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at the University of Texas MD Anderson Cancer Center utilized a functional annotation of mutations and fusions found in human cancers using two cell models, Ba/F3 (murine pro-B suspension cells) and MCF10A (human non-tumorigenic mammary epithelial cells). Read the abstract

University of Texas MD Anderson Cancer Center: Systematic Functional Annotation of Somatic Mutations in Cancer | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at the University of Texas MD Anderson Cancer Center utilized a functional annotation of mutations and fusions found in human cancers using two cell models, Ba/F3 (murine pro-B suspension cells) and MCF10A (human non-tumorigenic mammary epithelial cells). Read the abstract

Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions.

PubMed

Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Liewald, D C; Penke, L; Gale, C R; Deary, I J

2016-12-13

Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.

Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions

PubMed Central

Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Davies, Gail; Deary, Ian J; Debette, Stephanie; Verbaas, Carla I; Bressler, Jan; Schuur, Maaike; Smith, Albert V; Bis, Joshua C; Bennett, David A; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosley Jr, Thomas H; Liewald, D C; Penke, L; Gale, C R; Deary, I J

2016-01-01

Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions. PMID:27959336

A call for benchmarking transposable element annotation methods.

PubMed

Hoen, Douglas R; Hickey, Glenn; Bourque, Guillaume; Casacuberta, Josep; Cordaux, Richard; Feschotte, Cédric; Fiston-Lavier, Anna-Sophie; Hua-Van, Aurélie; Hubley, Robert; Kapusta, Aurélie; Lerat, Emmanuelle; Maumus, Florian; Pollock, David D; Quesneville, Hadi; Smit, Arian; Wheeler, Travis J; Bureau, Thomas E; Blanchette, Mathieu

2015-01-01

DNA derived from transposable elements (TEs) constitutes large parts of the genomes of complex eukaryotes, with major impacts not only on genomic research but also on how organisms evolve and function. Although a variety of methods and tools have been developed to detect and annotate TEs, there are as yet no standard benchmarks-that is, no standard way to measure or compare their accuracy. This lack of accuracy assessment calls into question conclusions from a wide range of research that depends explicitly or implicitly on TE annotation. In the absence of standard benchmarks, toolmakers are impeded in improving their tools, annotators cannot properly assess which tools might best suit their needs, and downstream researchers cannot judge how accuracy limitations might impact their studies. We therefore propose that the TE research community create and adopt standard TE annotation benchmarks, and we call for other researchers to join the authors in making this long-overdue effort a success.

SNPit: a federated data integration system for the purpose of functional SNP annotation

PubMed Central

Shen, Terry H; Carlson, Christopher S; Tarczy-Hornoch, Peter

2009-01-01

Genome wide association studies can potentially identify the genetic causes behind the majority of human diseases. With the advent of more advanced genotyping techniques, there is now an explosion of data gathered on single nucleotide polymorphisms (SNPs). The need exists for an integrated system that can provide up-to-date functional annotation information on SNPs. We have developed the SNP Integration Tool (SNPit) system to address this need. Built upon a federated data integration system, SNPit provides current information on a comprehensive list of SNP data sources. Additional logical inference analysis was included through an inference engine plug in. The SNPit web servlet is available online for use. SNPit allows users to go to one source for up-to-date information on the functional annotation of SNPs. A tool that can help to integrate and analyze the potential functional significance of SNPs is important for understanding the results from genome wide association studies. PMID:19327864

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

PubMed

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

2017-09-08

Oil palm is an important source of edible oil. The importance of the crop, as well as its long breeding cycle (10-12 years) has led to the sequencing of its genome in 2013 to pave the way for genomics-guided breeding. Nevertheless, the first set of gene predictions, although useful, had many fragmented genes. Classification and characterization of genes associated with traits of interest, such as those for fatty acid biosynthesis and disease resistance, were also limited. Lipid-, especially fatty acid (FA)-related genes are of particular interest for the oil palm as they specify oil yields and quality. This paper presents the characterization of the oil palm genome using different gene prediction methods and comparative genomics analysis, identification of FA biosynthesis and disease resistance genes, and the development of an annotation database and bioinformatics tools. Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC 3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC 3 -rich genes (GC 3  ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures. We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC 3 -rich and intronless), as well as those associated with important functions, such as FA biosynthesis and disease resistance. The study demonstrated the advantages of having an integrated approach to gene prediction and developed a computational framework for combining multiple genome annotations. These results, available in the oil palm annotation database ( http://palmxplore.mpob.gov.my ), will provide important resources for studies on the genomes of oil palm and related crops. This article was reviewed by Alexander Kel, Igor Rogozin, and Vladimir A. Kuznetsov.

GBshape: a genome browser database for DNA shape annotations

PubMed Central

Chiu, Tsu-Pei; Yang, Lin; Zhou, Tianyin; Main, Bradley J.; Parker, Stephen C.J.; Nuzhdin, Sergey V.; Tullius, Thomas D.; Rohs, Remo

2015-01-01

Many regulatory mechanisms require a high degree of specificity in protein-DNA binding. Nucleotide sequence does not provide an answer to the question of why a protein binds only to a small subset of the many putative binding sites in the genome that share the same core motif. Whereas higher-order effects, such as chromatin accessibility, cooperativity and cofactors, have been described, DNA shape recently gained attention as another feature that fine-tunes the DNA binding specificities of some transcription factor families. Our Genome Browser for DNA shape annotations (GBshape; freely available at http://rohslab.cmb.usc.edu/GBshape/) provides minor groove width, propeller twist, roll, helix twist and hydroxyl radical cleavage predictions for the entire genomes of 94 organisms. Additional genomes can easily be added using the GBshape framework. GBshape can be used to visualize DNA shape annotations qualitatively in a genome browser track format, and to download quantitative values of DNA shape features as a function of genomic position at nucleotide resolution. As biological applications, we illustrate the periodicity of DNA shape features that are present in nucleosome-occupied sequences from human, fly and worm, and we demonstrate structural similarities between transcription start sites in the genomes of four Drosophila species. PMID:25326329

MIPS: analysis and annotation of proteins from whole genomes

PubMed Central

Mewes, H. W.; Amid, C.; Arnold, R.; Frishman, D.; Güldener, U.; Mannhaupt, G.; Münsterkötter, M.; Pagel, P.; Strack, N.; Stümpflen, V.; Warfsmann, J.; Ruepp, A.

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein–protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:14681354

MIPS: analysis and annotation of proteins from whole genomes.

PubMed

Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

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

Prokaryotic Contig Annotation Pipeline Server: Web Application for a Prokaryotic Genome Annotation Pipeline Based on the Shiny App Package.

PubMed

Park, Byeonghyeok; Baek, Min-Jeong; Min, Byoungnam; Choi, In-Geol

2017-09-01

Genome annotation is a primary step in genomic research. To establish a light and portable prokaryotic genome annotation pipeline for use in individual laboratories, we developed a Shiny app package designated as "P-CAPS" (Prokaryotic Contig Annotation Pipeline Server). The package is composed of R and Python scripts that integrate publicly available annotation programs into a server application. P-CAPS is not only a browser-based interactive application but also a distributable Shiny app package that can be installed on any personal computer. The final annotation is provided in various standard formats and is summarized in an R markdown document. Annotation can be visualized and examined with a public genome browser. A benchmark test showed that the annotation quality and completeness of P-CAPS were reliable and compatible with those of currently available public pipelines.

Accessing the SEED genome databases via Web services API: tools for programmers.

PubMed

Disz, Terry; Akhter, Sajia; Cuevas, Daniel; Olson, Robert; Overbeek, Ross; Vonstein, Veronika; Stevens, Rick; Edwards, Robert A

2010-06-14

The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

The new modern era of yeast genomics: community sequencing and the resulting annotation of multiple Saccharomyces cerevisiae strains at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R.; Cherry, J. Michael

2013-01-01

The first completed eukaryotic genome sequence was that of the yeast Saccharomyces cerevisiae, and the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the original model organism database. SGD remains the authoritative community resource for the S. cerevisiae reference genome sequence and its annotation, and continues to provide comprehensive biological information correlated with S. cerevisiae genes and their products. A diverse set of yeast strains have been sequenced to explore commercial and laboratory applications, and a brief history of those strains is provided. The publication of these new genomes has motivated the creation of new tools, and SGD will annotate and provide comparative analyses of these sequences, correlating changes with variations in strain phenotypes and protein function. We are entering a new era at SGD, as we incorporate these new sequences and make them accessible to the scientific community, all in an effort to continue in our mission of educating researchers and facilitating discovery. Database URL: http://www.yeastgenome.org/ PMID:23487186

Escherichia coli K-12: a cooperatively developed annotation snapshot—2005

PubMed Central

Riley, Monica; Abe, Takashi; Arnaud, Martha B.; Berlyn, Mary K.B.; Blattner, Frederick R.; Chaudhuri, Roy R.; Glasner, Jeremy D.; Horiuchi, Takashi; Keseler, Ingrid M.; Kosuge, Takehide; Mori, Hirotada; Perna, Nicole T.; Plunkett, Guy; Rudd, Kenneth E.; Serres, Margrethe H.; Thomas, Gavin H.; Thomson, Nicholas R.; Wishart, David; Wanner, Barry L.

2006-01-01

The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles. PMID:16397293

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

PubMed

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

2014-05-01

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

VitisExpDB: a database resource for grape functional genomics.

PubMed

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-02-28

The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores approximately 320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of approximately 20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website http://cropdisease.ars.usda.gov/vitis_at/main-page.htm.

VitisExpDB: A database resource for grape functional genomics

PubMed Central

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-01-01

Background The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. Description VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores ~320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of ~20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. Conclusion The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website . PMID:18307813

Genome re-annotation: a wiki solution?

PubMed Central

Salzberg, Steven L

2007-01-01

The annotation of most genomes becomes outdated over time, owing in part to our ever-improving knowledge of genomes and in part to improvements in bioinformatics software. Unfortunately, annotation is rarely if ever updated and resources to support routine reannotation are scarce. Wiki software, which would allow many scientists to edit each genome's annotation, offers one possible solution. PMID:17274839

AGAPE (Automated Genome Analysis PipelinE) for Pan-Genome Analysis of Saccharomyces cerevisiae

PubMed Central

Song, Giltae; Dickins, Benjamin J. A.; Demeter, Janos; Engel, Stacia; Dunn, Barbara; Cherry, J. Michael

2015-01-01

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community. PMID:25781462

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

PubMed Central

Elsik, Christine G.; Tayal, Aditi; Diesh, Colin M.; Unni, Deepak R.; Emery, Marianne L.; Nguyen, Hung N.; Hagen, Darren E.

2016-01-01

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

Construction and Annotation of a High Density SNP Linkage Map of the Atlantic Salmon (Salmo salar) Genome.

PubMed

Tsai, Hsin Y; Robledo, Diego; Lowe, Natalie R; Bekaert, Michael; Taggart, John B; Bron, James E; Houston, Ross D

2016-07-07

High density linkage maps are useful tools for fine-scale mapping of quantitative trait loci, and characterization of the recombination landscape of a species' genome. Genomic resources for Atlantic salmon (Salmo salar) include a well-assembled reference genome, and high density single nucleotide polymorphism (SNP) arrays. Our aim was to create a high density linkage map, and to align it with the reference genome assembly. Over 96,000 SNPs were mapped and ordered on the 29 salmon linkage groups using a pedigreed population comprising 622 fish from 60 nuclear families, all genotyped with the 'ssalar01' high density SNP array. The number of SNPs per group showed a high positive correlation with physical chromosome length (r = 0.95). While the order of markers on the genetic and physical maps was generally consistent, areas of discrepancy were identified. Approximately 6.5% of the previously unmapped reference genome sequence was assigned to chromosomes using the linkage map. Male recombination rate was lower than females across the vast majority of the genome, but with a notable peak in subtelomeric regions. Finally, using RNA-Seq data to annotate the reference genome, the mapped SNPs were categorized according to their predicted function, including annotation of ∼2500 putative nonsynonymous variants. The highest density SNP linkage map for any salmonid species has been created, annotated, and integrated with the Atlantic salmon reference genome assembly. This map highlights the marked heterochiasmy of salmon, and provides a useful resource for salmonid genetics and genomics research. Copyright © 2016 Tsai et al.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation.

PubMed

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus F X

2007-08-30

Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from ftp://ftpmips.gsf.de/plants/apollo_webservice.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation

PubMed Central

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus FX

2007-01-01

Background Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. Results To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. Conclusion This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from . PMID:17760972

APPRIS: annotation of principal and alternative splice isoforms

PubMed Central

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. PMID:23161672

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

ASGARD: an open-access database of annotated transcriptomes for emerging model arthropod species.

PubMed

Zeng, Victor; Extavour, Cassandra G

2012-01-01

The increased throughput and decreased cost of next-generation sequencing (NGS) have shifted the bottleneck genomic research from sequencing to annotation, analysis and accessibility. This is particularly challenging for research communities working on organisms that lack the basic infrastructure of a sequenced genome, or an efficient way to utilize whatever sequence data may be available. Here we present a new database, the Assembled Searchable Giant Arthropod Read Database (ASGARD). This database is a repository and search engine for transcriptomic data from arthropods that are of high interest to multiple research communities but currently lack sequenced genomes. We demonstrate the functionality and utility of ASGARD using de novo assembled transcriptomes from the milkweed bug Oncopeltus fasciatus, the cricket Gryllus bimaculatus and the amphipod crustacean Parhyale hawaiensis. We have annotated these transcriptomes to assign putative orthology, coding region determination, protein domain identification and Gene Ontology (GO) term annotation to all possible assembly products. ASGARD allows users to search all assemblies by orthology annotation, GO term annotation or Basic Local Alignment Search Tool. User-friendly features of ASGARD include search term auto-completion suggestions based on database content, the ability to download assembly product sequences in FASTA format, direct links to NCBI data for predicted orthologs and graphical representation of the location of protein domains and matches to similar sequences from the NCBI non-redundant database. ASGARD will be a useful repository for transcriptome data from future NGS studies on these and other emerging model arthropods, regardless of sequencing platform, assembly or annotation status. This database thus provides easy, one-stop access to multi-species annotated transcriptome information. We anticipate that this database will be useful for members of multiple research communities, including developmental biology, physiology, evolutionary biology, ecology, comparative genomics and phylogenomics. Database URL: asgard.rc.fas.harvard.edu.

Improved maize reference genome with single-molecule technologies

USDA-ARS?s Scientific Manuscript database

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate elucidation of biological processes and support translation of research findings into improved and sustainable agricultural technolog...

Annotation and sequence diversity of transposable elements in common bean (Phaseolus vulgaris).

PubMed

Gao, Dongying; Abernathy, Brian; Rohksar, Daniel; Schmutz, Jeremy; Jackson, Scott A

2014-01-01

Common bean (Phaseolus vulgaris) is an important legume crop grown and consumed worldwide. With the availability of the common bean genome sequence, the next challenge is to annotate the genome and characterize functional DNA elements. Transposable elements (TEs) are the most abundant component of plant genomes and can dramatically affect genome evolution and genetic variation. Thus, it is pivotal to identify TEs in the common bean genome. In this study, we performed a genome-wide transposon annotation in common bean using a combination of homology and sequence structure-based methods. We developed a 2.12-Mb transposon database which includes 791 representative transposon sequences and is available upon request or from www.phytozome.org. Of note, nearly all transposons in the database are previously unrecognized TEs. More than 5,000 transposon-related expressed sequence tags (ESTs) were detected which indicates that some transposons may be transcriptionally active. Two Ty1-copia retrotransposon families were found to encode the envelope-like protein which has rarely been identified in plant genomes. Also, we identified an extra open reading frame (ORF) termed ORF2 from 15 Ty3-gypsy families that was located between the ORF encoding the retrotransposase and the 3'LTR. The ORF2 was in opposite transcriptional orientation to retrotransposase. Sequence homology searches and phylogenetic analysis suggested that the ORF2 may have an ancient origin, but its function is not clear. These transposon data provide a useful resource for understanding the genome organization and evolution and may be used to identify active TEs for developing transposon-tagging system in common bean and other related genomes.

[Advance on genome research of Yersinia pestis bacteriophage].

PubMed

Tan, H L; Wang, P; Li, W

2017-04-10

Completion of the genome sequences on Yersinia pestis bacteriophage offered unprecedented opportunity for researchers to carry out related genomic studies. This review was based on the genomic sequences and provided a genomic perspective in describing the essential features of genome on Yersinia pestis bacteriophage. Based on the comparative genomics, genetic evolutionary relationship was discussed. Description of functions from the gene prediction and protein annotation provided evidence for further related studies.

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context

PubMed Central

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-01-01

Background Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired. PMID:17877794

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

PubMed

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-09-18

Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

Phylogenetic and Protein Sequence Analysis of Bacterial Chemoreceptors.

PubMed

Ortega, Davi R; Zhulin, Igor B

2018-01-01

Identifying chemoreceptors in sequenced bacterial genomes, revealing their domain architecture, inferring their evolutionary relationships, and comparing them to chemoreceptors of known function become important steps in genome annotation and chemotaxis research. Here, we describe bioinformatics procedures that enable such analyses, using two closely related bacterial genomes as examples.

dbWGFP: a database and web server of human whole-genome single nucleotide variants and their functional predictions.

PubMed

Wu, Jiaxin; Wu, Mengmeng; Li, Lianshuo; Liu, Zhuo; Zeng, Wanwen; Jiang, Rui

2016-01-01

The recent advancement of the next generation sequencing technology has enabled the fast and low-cost detection of all genetic variants spreading across the entire human genome, making the application of whole-genome sequencing a tendency in the study of disease-causing genetic variants. Nevertheless, there still lacks a repository that collects predictions of functionally damaging effects of human genetic variants, though it has been well recognized that such predictions play a central role in the analysis of whole-genome sequencing data. To fill this gap, we developed a database named dbWGFP (a database and web server of human whole-genome single nucleotide variants and their functional predictions) that contains functional predictions and annotations of nearly 8.58 billion possible human whole-genome single nucleotide variants. Specifically, this database integrates 48 functional predictions calculated by 17 popular computational methods and 44 valuable annotations obtained from various data sources. Standalone software, user-friendly query services and free downloads of this database are available at http://bioinfo.au.tsinghua.edu.cn/dbwgfp. dbWGFP provides a valuable resource for the analysis of whole-genome sequencing, exome sequencing and SNP array data, thereby complementing existing data sources and computational resources in deciphering genetic bases of human inherited diseases. © The Author(s) 2016. Published by Oxford University Press.

Genome-wide analysis of tandem repeats in plants and green algae

Treesearch

Zhixin Zhao; Cheng Guo; Sreeskandarajan Sutharzan; Pei Li; Craig Echt; Jie Zhang; Chun Liang

2014-01-01

Tandem repeats (TRs) extensively exist in the genomes of prokaryotes and eukaryotes. Based on the sequenced genomes and gene annotations of 31 plant and algal species in Phytozome version 8.0 (http://www.phytozome.net/), we examined TRs in a genome-wide scale, characterized their distributions and motif features, and explored their putative biological functions. Among...

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. | Office of Cancer Genomics

Cancer.gov

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity.

Resequencing and annotation of the Nostoc punctiforme ATTC 29133 genome: facilitating biofuel and high-value chemical production

DOE PAGES

Moraes, Luis E.; Blow, Matthew J.; Hawley, Erik R.; ...

2017-02-16

Cyanobacteria have the potential to produce bulk and fine chemicals and members belonging to Nostoc sp. have received particular attention due to their relatively fast growth rate and the relative ease with which they can be harvested. Nostoc punctiforme is an aerobic, motile, Gram-negative, filamentous cyanobacterium that has been studied intensively to enhance our understanding of microbial carbon and nitrogen fixation. The genome of the type strain N. punctiforme ATCC 29133 was sequenced in 2001 and the scientific community has used these genome data extensively since then. Advances in bioinformatics tools for sequence annotation and the importance of this organismmore » prompted us to resequence and reanalyze its genome and to make both, the initial and improved annotation, available to the scientific community. The new draft genome has a total size of 9.1 Mbp and consists of 65 contiguous pieces of DNA with a GC content of 41.38% and 7664 protein-coding genes. Furthermore, the resequenced genome is slightly (5152 bp) larger and contains 987 more genes with functional prediction when compared to the previously published version. We deposited the annotation of both genomes in the Department of Energy’s IMG database to facilitate easy genome exploration by the scientific community without the need of in-depth bioinformatics skills. We expect that an facilitated access and ability to search the N. punctiforme ATCC 29133 for genes of interest will significantly facilitate metabolic engineering and genome prospecting efforts and ultimately the synthesis of biofuels and natural products from this keystone organism and closely related cyanobacteria.« less

Resequencing and annotation of the Nostoc punctiforme ATTC 29133 genome: facilitating biofuel and high-value chemical production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moraes, Luis E.; Blow, Matthew J.; Hawley, Erik R.

Cyanobacteria have the potential to produce bulk and fine chemicals and members belonging to Nostoc sp. have received particular attention due to their relatively fast growth rate and the relative ease with which they can be harvested. Nostoc punctiforme is an aerobic, motile, Gram-negative, filamentous cyanobacterium that has been studied intensively to enhance our understanding of microbial carbon and nitrogen fixation. The genome of the type strain N. punctiforme ATCC 29133 was sequenced in 2001 and the scientific community has used these genome data extensively since then. Advances in bioinformatics tools for sequence annotation and the importance of this organismmore » prompted us to resequence and reanalyze its genome and to make both, the initial and improved annotation, available to the scientific community. The new draft genome has a total size of 9.1 Mbp and consists of 65 contiguous pieces of DNA with a GC content of 41.38% and 7664 protein-coding genes. Furthermore, the resequenced genome is slightly (5152 bp) larger and contains 987 more genes with functional prediction when compared to the previously published version. We deposited the annotation of both genomes in the Department of Energy’s IMG database to facilitate easy genome exploration by the scientific community without the need of in-depth bioinformatics skills. We expect that an facilitated access and ability to search the N. punctiforme ATCC 29133 for genes of interest will significantly facilitate metabolic engineering and genome prospecting efforts and ultimately the synthesis of biofuels and natural products from this keystone organism and closely related cyanobacteria.« less

Enabling a Community to Dissect an Organism: Overview of the Neurospora Functional Genomics Project

PubMed Central

Dunlap, Jay C.; Borkovich, Katherine A.; Henn, Matthew R.; Turner, Gloria E.; Sachs, Matthew S.; Glass, N. Louise; McCluskey, Kevin; Plamann, Michael; Galagan, James E.; Birren, Bruce W.; Weiss, Richard L.; Townsend, Jeffrey P.; Loros, Jennifer J.; Nelson, Mary Anne; Lambreghts, Randy; Colot, Hildur V.; Park, Gyungsoon; Collopy, Patrick; Ringelberg, Carol; Crew, Christopher; Litvinkova, Liubov; DeCaprio, Dave; Hood, Heather M.; Curilla, Susan; Shi, Mi; Crawford, Matthew; Koerhsen, Michael; Montgomery, Phil; Larson, Lisa; Pearson, Matthew; Kasuga, Takao; Tian, Chaoguang; Baştürkmen, Meray; Altamirano, Lorena; Xu, Junhuan

2013-01-01

A consortium of investigators is engaged in a functional genomics project centered on the filamentous fungus Neurospora, with an eye to opening up the functional genomic analysis of all the filamentous fungi. The overall goal of the four interdependent projects in this effort is to acccomplish functional genomics, annotation, and expression analyses of Neurospora crassa, a filamentous fungus that is an established model for the assemblage of over 250,000 species of nonyeast fungi. Building from the completely sequenced 43-Mb Neurospora genome, Project 1 is pursuing the systematic disruption of genes through targeted gene replacements, phenotypic analysis of mutant strains, and their distribution to the scientific community at large. Project 2, through a primary focus in Annotation and Bioinformatics, has developed a platform for electronically capturing community feedback and data about the existing annotation, while building and maintaining a database to capture and display information about phenotypes. Oligonucleotide-based microarrays created in Project 3 are being used to collect baseline expression data for the nearly 11,000 distinguishable transcripts in Neurospora under various conditions of growth and development, and eventually to begin to analyze the global effects of loss of novel genes in strains created by Project 1. cDNA libraries generated in Project 4 document the overall complexity of expressed sequences in Neurospora, including alternative splicing alternative promoters and antisense transcripts. In addition, these studies have driven the assembly of an SNP map presently populated by nearly 300 markers that will greatly accelerate the positional cloning of genes. PMID:17352902

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

PubMed

Carroll, Ronan K; Weiss, Andy; Broach, William H; Wiemels, Richard E; Mogen, Austin B; Rice, Kelly C; Shaw, Lindsey N

2016-02-09

In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions. Despite a large number of studies identifying regulatory or small RNA (sRNA) genes in Staphylococcus aureus, their annotation is notably lacking in available genome files. In addition to this, there has been a considerable lack of cross-referencing in the wealth of studies identifying these elements, often leading to the same sRNA being identified multiple times and bearing multiple names. In this work, we have consolidated and curated known sRNA genes from the literature and mapped them to their position on the S. aureus genome, creating new genome annotation files. These files can now be used by the scientific community at large in experiments to search for previously undiscovered sRNA genes and to monitor sRNA gene expression by transcriptome sequencing (RNA-seq). We demonstrate this application, identifying 39 new sRNAs and studying their expression during S. aureus growth in human serum. Copyright © 2016 Carroll et al.

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

MitoFish and MiFish Pipeline: A Mitochondrial Genome Database of Fish with an Analysis Pipeline for Environmental DNA Metabarcoding.

PubMed

Sato, Yukuto; Miya, Masaki; Fukunaga, Tsukasa; Sado, Tetsuya; Iwasaki, Wataru

2018-06-01

Fish mitochondrial genome (mitogenome) data form a fundamental basis for revealing vertebrate evolution and hydrosphere ecology. Here, we report recent functional updates of MitoFish, which is a database of fish mitogenomes with a precise annotation pipeline MitoAnnotator. Most importantly, we describe implementation of MiFish pipeline for metabarcoding analysis of fish mitochondrial environmental DNA, which is a fast-emerging and powerful technology in fish studies. MitoFish, MitoAnnotator, and MiFish pipeline constitute a key platform for studies of fish evolution, ecology, and conservation, and are freely available at http://mitofish.aori.u-tokyo.ac.jp/ (last accessed April 7th, 2018).

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

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. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The Co-regulation Data Harvester: Automating gene annotation starting from a transcriptome database

NASA Astrophysics Data System (ADS)

Tsypin, Lev M.; Turkewitz, Aaron P.

Identifying co-regulated genes provides a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, a process much slower than genome sequencing per se. Tetrahymena thermophila, a unicellular eukaryote, has been a useful model organism and has a fully sequenced but sparsely annotated genome. One important resource for studying this organism has been an online transcriptomic database. We have developed an automated approach to gene annotation in the context of transcriptome data in T. thermophila, called the Co-regulation Data Harvester (CDH). Beginning with a gene of interest, the CDH identifies co-regulated genes by accessing the Tetrahymena transcriptome database. It then identifies their closely related genes (orthologs) in other organisms by using reciprocal BLAST searches. Finally, it collates the annotations of those orthologs' functions, which provides the user with information to help predict the cellular role of the initial query. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

Visualizing conserved gene location across microbe genomes

NASA Astrophysics Data System (ADS)

Shaw, Chris D.

2009-01-01

This paper introduces an analysis-based zoomable visualization technique for displaying the location of genes across many related species of microbes. The purpose of this visualizatiuon is to enable a biologist to examine the layout of genes in the organism of interest with respect to the gene organization of related organisms. During the genomic annotation process, the ability to observe gene organization in common with previously annotated genomes can help a biologist better confirm the structure and function of newly analyzed microbe DNA sequences. We have developed a visualization and analysis tool that enables the biologist to observe and examine gene organization among genomes, in the context of the primary sequence of interest. This paper describes the visualization and analysis steps, and presents a case study using a number of Rickettsia genomes.

CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison

PubMed Central

Castrignanò, Tiziana; Canali, Alessandro; Grillo, Giorgio; Liuni, Sabino; Mignone, Flavio; Pesole, Graziano

2004-01-01

The identification and characterization of genome tracts that are highly conserved across species during evolution may contribute significantly to the functional annotation of whole-genome sequences. Indeed, such sequences are likely to correspond to known or unknown coding exons or regulatory motifs. Here, we present a web server implementing a previously developed algorithm that, by comparing user-submitted genome sequences, is able to identify statistically significant conserved blocks and assess their coding or noncoding nature through the measure of a coding potential score. The web tool, available at http://www.caspur.it/CSTminer/, is dynamically interconnected with the Ensembl genome resources and produces a graphical output showing a map of detected conserved sequences and annotated gene features. PMID:15215464

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

PubMed

Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

2016-01-04

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

First generation annotations for the fathead minnow (Pimephales promelas) genome

EPA Science Inventory

Ab initio gene prediction and evidence alignment were used to produce the first annotations for the fathead minnow SOAPdenovo genome assembly. Additionally, a genome browser hosted at genome.setac.org provides simplified access to the annotation data in context with fathead minno...

The Paris-Sud yeast structural genomics pilot-project: from structure to function.

PubMed

Quevillon-Cheruel, Sophie; Liger, Dominique; Leulliot, Nicolas; Graille, Marc; Poupon, Anne; Li de La Sierra-Gallay, Inès; Zhou, Cong-Zhao; Collinet, Bruno; Janin, Joël; Van Tilbeurgh, Herman

2004-01-01

We present here the outlines and results from our yeast structural genomics (YSG) pilot-project. A lab-scale platform for the systematic production and structure determination is presented. In order to validate this approach, 250 non-membrane proteins of unknown structure were targeted. Strategies and final statistics are evaluated. We finally discuss the opportunity of structural genomics programs to contribute to functional biochemical annotation.

SorghumFDB: sorghum functional genomics database with multidimensional network analysis.

PubMed

Tian, Tian; You, Qi; Zhang, Liwei; Yi, Xin; Yan, Hengyu; Xu, Wenying; Su, Zhen

2016-01-01

Sorghum (Sorghum bicolor [L.] Moench) has excellent agronomic traits and biological properties, such as heat and drought-tolerance. It is a C4 grass and potential bioenergy-producing plant, which makes it an important crop worldwide. With the sorghum genome sequence released, it is essential to establish a sorghum functional genomics data mining platform. We collected genomic data and some functional annotations to construct a sorghum functional genomics database (SorghumFDB). SorghumFDB integrated knowledge of sorghum gene family classifications (transcription regulators/factors, carbohydrate-active enzymes, protein kinases, ubiquitins, cytochrome P450, monolignol biosynthesis related enzymes, R-genes and organelle-genes), detailed gene annotations, miRNA and target gene information, orthologous pairs in the model plants Arabidopsis, rice and maize, gene loci conversions and a genome browser. We further constructed a dynamic network of multidimensional biological relationships, comprised of the co-expression data, protein-protein interactions and miRNA-target pairs. We took effective measures to combine the network, gene set enrichment and motif analyses to determine the key regulators that participate in related metabolic pathways, such as the lignin pathway, which is a major biological process in bioenergy-producing plants.Database URL: http://structuralbiology.cau.edu.cn/sorghum/index.html. © The Author(s) 2016. Published by Oxford University Press.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

Specialized microbial databases for inductive exploration of microbial genome sequences

PubMed Central

Fang, Gang; Ho, Christine; Qiu, Yaowu; Cubas, Virginie; Yu, Zhou; Cabau, Cédric; Cheung, Frankie; Moszer, Ivan; Danchin, Antoine

2005-01-01

Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison. PMID:15698474

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuo, Alan; Grigoriev, Igor

2009-04-17

Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentousmore » ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.« less

Seshat: A Web service for accurate annotation, validation, and analysis of TP53 variants generated by conventional and next-generation sequencing.

PubMed

Tikkanen, Tuomas; Leroy, Bernard; Fournier, Jean Louis; Risques, Rosa Ana; Malcikova, Jitka; Soussi, Thierry

2018-07-01

Accurate annotation of genomic variants in human diseases is essential to allow personalized medicine. Assessment of somatic and germline TP53 alterations has now reached the clinic and is required in several circumstances such as the identification of the most effective cancer therapy for patients with chronic lymphocytic leukemia (CLL). Here, we present Seshat, a Web service for annotating TP53 information derived from sequencing data. A flexible framework allows the use of standard file formats such as Mutation Annotation Format (MAF) or Variant Call Format (VCF), as well as common TXT files. Seshat performs accurate variant annotations using the Human Genome Variation Society (HGVS) nomenclature and the stable TP53 genomic reference provided by the Locus Reference Genomic (LRG). In addition, using the 2017 release of the UMD_TP53 database, Seshat provides multiple statistical information for each TP53 variant including database frequency, functional activity, or pathogenicity. The information is delivered in standardized output tables that minimize errors and facilitate comparison of mutational data across studies. Seshat is a beneficial tool to interpret the ever-growing TP53 sequencing data generated by multiple sequencing platforms and it is freely available via the TP53 Website, http://p53.fr or directly at http://vps338341.ovh.net/. © 2018 Wiley Periodicals, Inc.

GBshape: a genome browser database for DNA shape annotations.

PubMed

Chiu, Tsu-Pei; Yang, Lin; Zhou, Tianyin; Main, Bradley J; Parker, Stephen C J; Nuzhdin, Sergey V; Tullius, Thomas D; Rohs, Remo

2015-01-01

Many regulatory mechanisms require a high degree of specificity in protein-DNA binding. Nucleotide sequence does not provide an answer to the question of why a protein binds only to a small subset of the many putative binding sites in the genome that share the same core motif. Whereas higher-order effects, such as chromatin accessibility, cooperativity and cofactors, have been described, DNA shape recently gained attention as another feature that fine-tunes the DNA binding specificities of some transcription factor families. Our Genome Browser for DNA shape annotations (GBshape; freely available at http://rohslab.cmb.usc.edu/GBshape/) provides minor groove width, propeller twist, roll, helix twist and hydroxyl radical cleavage predictions for the entire genomes of 94 organisms. Additional genomes can easily be added using the GBshape framework. GBshape can be used to visualize DNA shape annotations qualitatively in a genome browser track format, and to download quantitative values of DNA shape features as a function of genomic position at nucleotide resolution. As biological applications, we illustrate the periodicity of DNA shape features that are present in nucleosome-occupied sequences from human, fly and worm, and we demonstrate structural similarities between transcription start sites in the genomes of four Drosophila species. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

GenomeHubs: simple containerized setup of a custom Ensembl database and web server for any species

PubMed Central

Kumar, Sujai; Stevens, Lewis; Blaxter, Mark

2017-01-01

Abstract As the generation and use of genomic datasets is becoming increasingly common in all areas of biology, the need for resources to collate, analyse and present data from one or more genome projects is becoming more pressing. The Ensembl platform is a powerful tool to make genome data and cross-species analyses easily accessible through a web interface and a comprehensive application programming interface. Here we introduce GenomeHubs, which provide a containerized environment to facilitate the setup and hosting of custom Ensembl genome browsers. This simplifies mirroring of existing content and import of new genomic data into the Ensembl database schema. GenomeHubs also provide a set of analysis containers to decorate imported genomes with results of standard analyses and functional annotations and support export to flat files, including EMBL format for submission of assemblies and annotations to International Nucleotide Sequence Database Collaboration. Database URL: http://GenomeHubs.org PMID:28605774

Long-read sequencing of chicken transcripts and identification of new transcript isoforms.

PubMed

Thomas, Sean; Underwood, Jason G; Tseng, Elizabeth; Holloway, Alisha K

2014-01-01

The chicken has long served as an important model organism in many fields, and continues to aid our understanding of animal development. Functional genomics studies aimed at probing the mechanisms that regulate development require high-quality genomes and transcript annotations. The quality of these resources has improved dramatically over the last several years, but many isoforms and genes have yet to be identified. We hope to contribute to the process of improving these resources with the data presented here: a set of long cDNA sequencing reads, and a curated set of new genes and transcript isoforms not currently represented in the most up-to-date genome annotation currently available to the community of researchers who rely on the chicken genome.

Family-specific scaling laws in bacterial genomes.

PubMed

De Lazzari, Eleonora; Grilli, Jacopo; Maslov, Sergei; Cosentino Lagomarsino, Marco

2017-07-27

Among several quantitative invariants found in evolutionary genomics, one of the most striking is the scaling of the overall abundance of proteins, or protein domains, sharing a specific functional annotation across genomes of given size. The size of these functional categories change, on average, as power-laws in the total number of protein-coding genes. Here, we show that such regularities are not restricted to the overall behavior of high-level functional categories, but also exist systematically at the level of single evolutionary families of protein domains. Specifically, the number of proteins within each family follows family-specific scaling laws with genome size. Functionally similar sets of families tend to follow similar scaling laws, but this is not always the case. To understand this systematically, we provide a comprehensive classification of families based on their scaling properties. Additionally, we develop a quantitative score for the heterogeneity of the scaling of families belonging to a given category or predefined group. Under the common reasonable assumption that selection is driven solely or mainly by biological function, these findings point to fine-tuned and interdependent functional roles of specific protein domains, beyond our current functional annotations. This analysis provides a deeper view on the links between evolutionary expansion of protein families and the functional constraints shaping the gene repertoire of bacterial genomes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

DOE PAGES

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos; ...

2016-02-24

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos

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

JGI Plant Genomics Gene Annotation Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shu, Shengqiang; Rokhsar, Dan; Goodstein, David

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 thismore » 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.« less

TabSQL: a MySQL tool to facilitate mapping user data to public databases.

PubMed

Xia, Xiao-Qin; McClelland, Michael; Wang, Yipeng

2010-06-23

With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data.

TabSQL: a MySQL tool to facilitate mapping user data to public databases

PubMed Central

2010-01-01

Background With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. Results We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. Conclusions TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data. PMID:20573251

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

USDA-ARS?s Scientific Manuscript database

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

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.

PubMed

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. © 2015 American Society of Plant Biologists. All Rights Reserved.

ISEScan: automated identification of insertion sequence elements in prokaryotic genomes.

PubMed

Xie, Zhiqun; Tang, Haixu

2017-11-01

The insertion sequence (IS) elements are the smallest but most abundant autonomous transposable elements in prokaryotic genomes, which play a key role in prokaryotic genome organization and evolution. With the fast growing genomic data, it is becoming increasingly critical for biology researchers to be able to accurately and automatically annotate ISs in prokaryotic genome sequences. The available automatic IS annotation systems are either providing only incomplete IS annotation or relying on the availability of existing genome annotations. Here, we present a new IS elements annotation pipeline to address these issues. ISEScan is a highly sensitive software pipeline based on profile hidden Markov models constructed from manually curated IS elements. ISEScan performs better than existing IS annotation systems when tested on prokaryotic genomes with curated annotations of IS elements. Applying it to 2784 prokaryotic genomes, we report the global distribution of IS families across taxonomic clades in Archaea and Bacteria. ISEScan is implemented in Python and released as an open source software at https://github.com/xiezhq/ISEScan. hatang@indiana.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Improvement of genome assembly completeness and identification of novel full-length protein-coding genes by RNA-seq in the giant panda genome.

PubMed

Chen, Meili; Hu, Yibo; Liu, Jingxing; Wu, Qi; Zhang, Chenglin; Yu, Jun; Xiao, Jingfa; Wei, Fuwen; Wu, Jiayan

2015-12-11

High-quality and complete gene models are the basis of whole genome analyses. The giant panda (Ailuropoda melanoleuca) genome was the first genome sequenced on the basis of solely short reads, but the genome annotation had lacked the support of transcriptomic evidence. In this study, we applied RNA-seq to globally improve the genome assembly completeness and to detect novel expressed transcripts in 12 tissues from giant pandas, by using a transcriptome reconstruction strategy that combined reference-based and de novo methods. Several aspects of genome assembly completeness in the transcribed regions were effectively improved by the de novo assembled transcripts, including genome scaffolding, the detection of small-size assembly errors, the extension of scaffold/contig boundaries, and gap closure. Through expression and homology validation, we detected three groups of novel full-length protein-coding genes. A total of 12.62% of the novel protein-coding genes were validated by proteomic data. GO annotation analysis showed that some of the novel protein-coding genes were involved in pigmentation, anatomical structure formation and reproduction, which might be related to the development and evolution of the black-white pelage, pseudo-thumb and delayed embryonic implantation of giant pandas. The updated genome annotation will help further giant panda studies from both structural and functional perspectives.

Wheat EST resources for functional genomics of abiotic stress

PubMed Central

Houde, Mario; Belcaid, Mahdi; Ouellet, François; Danyluk, Jean; Monroy, Antonio F; Dryanova, Ani; Gulick, Patrick; Bergeron, Anne; Laroche, André; Links, Matthew G; MacCarthy, Luke; Crosby, William L; Sarhan, Fathey

2006-01-01

Background Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. Results We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. Conclusion We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals. PMID:16772040

SG-ADVISER mtDNA: a web server for mitochondrial DNA annotation with data from 200 samples of a healthy aging cohort.

PubMed

Rueda, Manuel; Torkamani, Ali

2017-08-18

Whole genome and exome sequencing usually include reads containing mitochondrial DNA (mtDNA). Yet, state-of-the-art pipelines and services for human nuclear genome variant calling and annotation do not handle mitochondrial genome data appropriately. As a consequence, any researcher desiring to add mtDNA variant analysis to their investigations is forced to explore the literature for mtDNA pipelines, evaluate them, and implement their own instance of the desired tool. This task is far from trivial, and can be prohibitive for non-bioinformaticians. We have developed SG-ADVISER mtDNA, a web server to facilitate the analysis and interpretation of mtDNA genomic data coming from next generation sequencing (NGS) experiments. The server was built in the context of our SG-ADVISER framework and on top of the MtoolBox platform (Calabrese et al., Bioinformatics 30(21):3115-3117, 2014), and includes most of its functionalities (i.e., assembly of mitochondrial genomes, heteroplasmic fractions, haplogroup assignment, functional and prioritization analysis of mitochondrial variants) as well as a back-end and a front-end interface. The server has been tested with unpublished data from 200 individuals of a healthy aging cohort (Erikson et al., Cell 165(4):1002-1011, 2016) and their data is made publicly available here along with a preliminary analysis of the variants. We observed that individuals over ~90 years old carried low levels of heteroplasmic variants in their genomes. SG-ADVISER mtDNA is a fast and functional tool that allows for variant calling and annotation of human mtDNA data coming from NGS experiments. The server was built with simplicity in mind, and builds on our own experience in interpreting mtDNA variants in the context of sudden death and rare diseases. Our objective is to provide an interface for non-bioinformaticians aiming to acquire (or contrast) mtDNA annotations via MToolBox. SG-ADVISER web server is freely available to all users at https://genomics.scripps.edu/mtdna .

Functional sequencing read annotation for high precision microbiome analysis

PubMed Central

Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani; Vaysberg, Pavel; Rühlemann, Malte C; Wu, Guojun; Heinsen, Femke-Anouska; Tempel, Marie; Zhao, Liping; Lieb, Wolfgang; Franke, Andre; Bromberg, Yana

2018-01-01

Abstract The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it. PMID:29194524

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

PubMed

St Laurent, Georges; 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

2016-04-20

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 vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA 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. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data.

PubMed

Fiston-Lavier, Anna-Sophie; Barrón, Maite G; Petrov, Dmitri A; González, Josefa

2015-02-27

Transposable elements (TEs) constitute the most active, diverse and ancient component in a broad range of genomes. Complete understanding of genome function and evolution cannot be achieved without a thorough understanding of TE impact and biology. However, in-depth analysis of TEs still represents a challenge due to the repetitive nature of these genomic entities. In this work, we present a broadly applicable and flexible tool: T-lex2. T-lex2 is the only available software that allows routine, automatic and accurate genotyping of individual TE insertions and estimation of their population frequencies both using individual strain and pooled next-generation sequencing data. Furthermore, T-lex2 also assesses the quality of the calls allowing the identification of miss-annotated TEs and providing the necessary information to re-annotate them. The flexible and customizable design of T-lex2 allows running it in any genome and for any type of TE insertion. Here, we tested the fidelity of T-lex2 using the fly and human genomes. Overall, T-lex2 represents a significant improvement in our ability to analyze the contribution of TEs to genome function and evolution as well as learning about the biology of TEs. T-lex2 is freely available online at http://sourceforge.net/projects/tlex. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease

PubMed Central

2012-01-01

The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org. PMID:23013645

VESPA: Software to Facilitate Genomic Annotation of Prokaryotic Organisms Through Integration of Proteomic and Transcriptomic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Elena S.; McCue, Lee Ann; Rutledge, Alexandra C.

2012-04-25

Visual Exploration and Statistics to Promote Annotation (VESPA) is an interactive visual analysis software tool that facilitates the discovery of structural mis-annotations in prokaryotic genomes. VESPA integrates high-throughput peptide-centric proteomics data and oligo-centric or RNA-Seq transcriptomics data into a genomic context. The data may be interrogated via visual analysis across multiple levels of genomic resolution, linked searches, exports and interaction with BLAST to rapidly identify location of interest within the genome and evaluate potential mis-annotations.

KEGG orthology-based annotation of the predicted proteome of Acropora digitifera: ZoophyteBase - an open access and searchable database of a coral genome

PubMed Central

2013-01-01

Background Contemporary coral reef research has firmly established that a genomic approach is urgently needed to better understand the effects of anthropogenic environmental stress and global climate change on coral holobiont interactions. Here we present KEGG orthology-based annotation of the complete genome sequence of the scleractinian coral Acropora digitifera and provide the first comprehensive view of the genome of a reef-building coral by applying advanced bioinformatics. Description Sequences from the KEGG database of protein function were used to construct hidden Markov models. These models were used to search the predicted proteome of A. digitifera to establish complete genomic annotation. The annotated dataset is published in ZoophyteBase, an open access format with different options for searching the data. A particularly useful feature is the ability to use a Google-like search engine that links query words to protein attributes. We present features of the annotation that underpin the molecular structure of key processes of coral physiology that include (1) regulatory proteins of symbiosis, (2) planula and early developmental proteins, (3) neural messengers, receptors and sensory proteins, (4) calcification and Ca2+-signalling proteins, (5) plant-derived proteins, (6) proteins of nitrogen metabolism, (7) DNA repair proteins, (8) stress response proteins, (9) antioxidant and redox-protective proteins, (10) proteins of cellular apoptosis, (11) microbial symbioses and pathogenicity proteins, (12) proteins of viral pathogenicity, (13) toxins and venom, (14) proteins of the chemical defensome and (15) coral epigenetics. Conclusions We advocate that providing annotation in an open-access searchable database available to the public domain will give an unprecedented foundation to interrogate the fundamental molecular structure and interactions of coral symbiosis and allow critical questions to be addressed at the genomic level based on combined aspects of evolutionary, developmental, metabolic, and environmental perspectives. PMID:23889801

Global analysis of bacterial transcription factors to predict cellular target processes.

PubMed

Doerks, Tobias; Andrade, Miguel A; Lathe, Warren; von Mering, Christian; Bork, Peer

2004-03-01

Whole-genome sequences are now available for >100 bacterial species, giving unprecedented power to comparative genomics approaches. We have applied genome-context methods to predict target processes that are regulated by transcription factors (TFs). Of 128 orthologous groups of proteins annotated as TFs, to date, 36 are functionally uncharacterized; in our analysis we predict a probable cellular target process or biochemical pathway for half of these functionally uncharacterized TFs.

Genome-wide characterization of centromeric satellites from multiple mammalian genomes.

PubMed

Alkan, Can; Cardone, Maria Francesca; Catacchio, Claudia Rita; Antonacci, Francesca; O'Brien, Stephen J; Ryder, Oliver A; Purgato, Stefania; Zoli, Monica; Della Valle, Giuliano; Eichler, Evan E; Ventura, Mario

2011-01-01

Despite its importance in cell biology and evolution, the centromere has remained the final frontier in genome assembly and annotation due to its complex repeat structure. However, isolation and characterization of the centromeric repeats from newly sequenced species are necessary for a complete understanding of genome evolution and function. In recent years, various genomes have been sequenced, but the characterization of the corresponding centromeric DNA has lagged behind. Here, we present a computational method (RepeatNet) to systematically identify higher-order repeat structures from unassembled whole-genome shotgun sequence and test whether these sequence elements correspond to functional centromeric sequences. We analyzed genome datasets from six species of mammals representing the diversity of the mammalian lineage, namely, horse, dog, elephant, armadillo, opossum, and platypus. We define candidate monomer satellite repeats and demonstrate centromeric localization for five of the six genomes. Our analysis revealed the greatest diversity of centromeric sequences in horse and dog in contrast to elephant and armadillo, which showed high-centromeric sequence homogeneity. We could not isolate centromeric sequences within the platypus genome, suggesting that centromeres in platypus are not enriched in satellite DNA. Our method can be applied to the characterization of thousands of other vertebrate genomes anticipated for sequencing in the near future, providing an important tool for annotation of centromeres.

The 'dark matter' in the plant genomes: non-coding and unannotated DNA sequences associated with open chromatin.

PubMed

Jiang, Jiming

2015-04-01

Sequencing of complete plant genomes has become increasingly more routine since the advent of the next-generation sequencing technology. Identification and annotation of large amounts of noncoding but functional DNA sequences, including cis-regulatory DNA elements (CREs), have become a new frontier in plant genome research. Genomic regions containing active CREs bound to regulatory proteins are hypersensitive to DNase I digestion and are called DNase I hypersensitive sites (DHSs). Several recent DHS studies in plants illustrate that DHS datasets produced by DNase I digestion followed by next-generation sequencing (DNase-seq) are highly valuable for the identification and characterization of CREs associated with plant development and responses to environmental cues. DHS-based genomic profiling has opened a door to identify and annotate the 'dark matter' in sequenced plant genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

EcoGene 3.0

PubMed Central

Zhou, Jindan; Rudd, Kenneth E.

2013-01-01

EcoGene (http://ecogene.org) is a database and website devoted to continuously improving the structural and functional annotation of Escherichia coli K-12, one of the most well understood model organisms, represented by the MG1655(Seq) genome sequence and annotations. Major improvements to EcoGene in the past decade include (i) graphic presentations of genome map features; (ii) ability to design Boolean queries and Venn diagrams from EcoArray, EcoTopics or user-provided GeneSets; (iii) the genome-wide clone and deletion primer design tool, PrimerPairs; (iv) sequence searches using a customized EcoBLAST; (v) a Cross Reference table of synonymous gene and protein identifiers; (vi) proteome-wide indexing with GO terms; (vii) EcoTools access to >2000 complete bacterial genomes in EcoGene-RefSeq; (viii) establishment of a MySql relational database; and (ix) use of web content management systems. The biomedical literature is surveyed daily to provide citation and gene function updates. As of September 2012, the review of 37 397 abstracts and articles led to creation of 98 425 PubMed-Gene links and 5415 PubMed-Topic links. Annotation updates to Genbank U00096 are transmitted from EcoGene to NCBI. Experimental verifications include confirmation of a CTG start codon, pseudogene restoration and quality assurance of the Keio strain collection. PMID:23197660

EcoGene 3.0.

PubMed

Zhou, Jindan; Rudd, Kenneth E

2013-01-01

EcoGene (http://ecogene.org) is a database and website devoted to continuously improving the structural and functional annotation of Escherichia coli K-12, one of the most well understood model organisms, represented by the MG1655(Seq) genome sequence and annotations. Major improvements to EcoGene in the past decade include (i) graphic presentations of genome map features; (ii) ability to design Boolean queries and Venn diagrams from EcoArray, EcoTopics or user-provided GeneSets; (iii) the genome-wide clone and deletion primer design tool, PrimerPairs; (iv) sequence searches using a customized EcoBLAST; (v) a Cross Reference table of synonymous gene and protein identifiers; (vi) proteome-wide indexing with GO terms; (vii) EcoTools access to >2000 complete bacterial genomes in EcoGene-RefSeq; (viii) establishment of a MySql relational database; and (ix) use of web content management systems. The biomedical literature is surveyed daily to provide citation and gene function updates. As of September 2012, the review of 37 397 abstracts and articles led to creation of 98 425 PubMed-Gene links and 5415 PubMed-Topic links. Annotation updates to Genbank U00096 are transmitted from EcoGene to NCBI. Experimental verifications include confirmation of a CTG start codon, pseudogene restoration and quality assurance of the Keio strain collection.

Increased alignment sensitivity improves the usage of genome alignments for comparative gene annotation.

PubMed

Sharma, Virag; Hiller, Michael

2017-08-21

Genome alignments provide a powerful basis to transfer gene annotations from a well-annotated reference genome to many other aligned genomes. The completeness of these annotations crucially depends on the sensitivity of the underlying genome alignment. Here, we investigated the impact of the genome alignment parameters and found that parameters with a higher sensitivity allow the detection of thousands of novel alignments between orthologous exons that have been missed before. In particular, comparisons between species separated by an evolutionary distance of >0.75 substitutions per neutral site, like human and other non-placental vertebrates, benefit from increased sensitivity. To systematically test if increased sensitivity improves comparative gene annotations, we built a multiple alignment of 144 vertebrate genomes and used this alignment to map human genes to the other 143 vertebrates with CESAR. We found that higher alignment sensitivity substantially improves the completeness of comparative gene annotations by adding on average 2382 and 7440 novel exons and 117 and 317 novel genes for mammalian and non-mammalian species, respectively. Our results suggest a more sensitive alignment strategy that should generally be used for genome alignments between distantly-related species. Our 144-vertebrate genome alignment and the comparative gene annotations (https://bds.mpi-cbg.de/hillerlab/144VertebrateAlignment_CESAR/) are a valuable resource for comparative genomics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea.

PubMed

Makarova, Kira S; Sorokin, Alexander V; Novichkov, Pavel S; Wolf, Yuri I; Koonin, Eugene V

2007-11-27

An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs). Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes. New Archaeal Clusters of Orthologous Genes (arCOGs) were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon) using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover approximately 88% of the genes in a genome compared to a approximately 76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; approximately 40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome) consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA) is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile that, in addition to the core archaeal functions, encoded more idiosyncratic systems, e.g., the CASS systems of antivirus defense and some toxin-antitoxin systems. The arCOGs provide a convenient, flexible framework for functional annotation of archaeal genomes, comparative genomics and evolutionary reconstructions. Genomic reconstructions suggest that the last common ancestor of archaea might have been (nearly) as advanced as the modern archaeal hyperthermophiles. ArCOGs and related information are available at: ftp://ftp.ncbi.nih.gov/pub/koonin/arCOGs/.

The majority of total nuclear-encoded non-ribosomal RNA in a human cell is 'dark matter' un-annotated RNA.

PubMed

Kapranov, Philipp; St Laurent, Georges; Raz, Tal; Ozsolak, Fatih; Reynolds, C Patrick; Sorensen, Poul H B; Reaman, Gregory; Milos, Patrice; Arceci, Robert J; Thompson, John F; Triche, Timothy J

2010-12-21

Discovery that the transcriptional output of the human genome is far more complex than predicted by the current set of protein-coding annotations and that most RNAs produced do not appear to encode proteins has transformed our understanding of genome complexity and suggests new paradigms of genome regulation. However, the fraction of all cellular RNA whose function we do not understand and the fraction of the genome that is utilized to produce that RNA remain controversial. This is not simply a bookkeeping issue because the degree to which this un-annotated transcription is present has important implications with respect to its biologic function and to the general architecture of genome regulation. For example, efforts to elucidate how non-coding RNAs (ncRNAs) regulate genome function will be compromised if that class of RNAs is dismissed as simply 'transcriptional noise'. We show that the relative mass of RNA whose function and/or structure we do not understand (the so called 'dark matter' RNAs), as a proportion of all non-ribosomal, non-mitochondrial human RNA (mt-RNA), can be greater than that of protein-encoding transcripts. This observation is obscured in studies that focus only on polyA-selected RNA, a method that enriches for protein coding RNAs and at the same time discards the vast majority of RNA prior to analysis. We further show the presence of a large number of very long, abundantly-transcribed regions (100's of kb) in intergenic space and further show that expression of these regions is associated with neoplastic transformation. These overlap some regions found previously in normal human embryonic tissues and raises an interesting hypothesis as to the function of these ncRNAs in both early development and neoplastic transformation. We conclude that 'dark matter' RNA can constitute the majority of non-ribosomal, non-mitochondrial-RNA and a significant fraction arises from numerous very long, intergenic transcribed regions that could be involved in neoplastic transformation.

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

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). © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

Sputnik: a database platform for comparative plant genomics.

PubMed

Rudd, Stephen; Mewes, Hans-Werner; Mayer, Klaus F X

2003-01-01

Two million plant ESTs, from 20 different plant species, and totalling more than one 1000 Mbp of DNA sequence, represents a formidable transcriptomic resource. Sputnik uses the potential of this sequence resource to fill some of the information gap in the un-sequenced plant genomes and to serve as the foundation for in silicio comparative plant genomics. The complexity of the individual EST collections has been reduced using optimised EST clustering techniques. Annotation of cluster sequences is performed by exploiting and transferring information from the comprehensive knowledgebase already produced for the completed model plant genome (Arabidopsis thaliana) and by performing additional state of-the-art sequence analyses relevant to today's plant biologist. Functional predictions, comparative analyses and associative annotations for 500 000 plant EST derived peptides make Sputnik (http://mips.gsf.de/proj/sputnik/) a valid platform for contemporary plant genomics.

Sputnik: a database platform for comparative plant genomics

PubMed Central

Rudd, Stephen; Mewes, Hans-Werner; Mayer, Klaus F.X.

2003-01-01

Two million plant ESTs, from 20 different plant species, and totalling more than one 1000 Mbp of DNA sequence, represents a formidable transcriptomic resource. Sputnik uses the potential of this sequence resource to fill some of the information gap in the un-sequenced plant genomes and to serve as the foundation for in silicio comparative plant genomics. The complexity of the individual EST collections has been reduced using optimised EST clustering techniques. Annotation of cluster sequences is performed by exploiting and transferring information from the comprehensive knowledgebase already produced for the completed model plant genome (Arabidopsis thaliana) and by performing additional state of-the-art sequence analyses relevant to today's plant biologist. Functional predictions, comparative analyses and associative annotations for 500 000 plant EST derived peptides make Sputnik (http://mips.gsf.de/proj/sputnik/) a valid platform for contemporary plant genomics. PMID:12519965

Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs).

PubMed

Natale, D A; Shankavaram, U T; Galperin, M Y; Wolf, Y I; Aravind, L; Koonin, E V

2000-01-01

Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and predicted protein functions provide for a significant improvement in genome annotation. A differential genome display approach helps in a systematic investigation of common and distinct features of gene repertoires and in some cases reveals unexpected connections that may be indicative of functional similarities between phylogenetically distant organisms and of lateral gene exchange.

Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs)

PubMed Central

Natale, Darren A; Shankavaram, Uma T; Galperin, Michael Y; Wolf, Yuri I; Aravind, L; Koonin, Eugene V

2000-01-01

Background: Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. Results: A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Conclusions: Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and predicted protein functions provide for a significant improvement in genome annotation. A differential genome display approach helps in a systematic investigation of common and distinct features of gene repertoires and in some cases reveals unexpected connections that may be indicative of functional similarities between phylogenetically distant organisms and of lateral gene exchange. PMID:11178258

Next Generation Models for Storage and Representation of Microbial Biological Annotation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quest, Daniel J; Land, Miriam L; Brettin, Thomas S

2010-01-01

Background Traditional genome annotation systems were developed in a very different computing era, one where the World Wide Web was just emerging. Consequently, these systems are built as centralized black boxes focused on generating high quality annotation submissions to GenBank/EMBL supported by expert manual curation. The exponential growth of sequence data drives a growing need for increasingly higher quality and automatically generated annotation. Typical annotation pipelines utilize traditional database technologies, clustered computing resources, Perl, C, and UNIX file systems to process raw sequence data, identify genes, and predict and categorize gene function. These technologies tightly couple the annotation software systemmore » to hardware and third party software (e.g. relational database systems and schemas). This makes annotation systems hard to reproduce, inflexible to modification over time, difficult to assess, difficult to partition across multiple geographic sites, and difficult to understand for those who are not domain experts. These systems are not readily open to scrutiny and therefore not scientifically tractable. The advent of Semantic Web standards such as Resource Description Framework (RDF) and OWL Web Ontology Language (OWL) enables us to construct systems that address these challenges in a new comprehensive way. Results Here, we develop a framework for linking traditional data to OWL-based ontologies in genome annotation. We show how data standards can decouple hardware and third party software tools from annotation pipelines, thereby making annotation pipelines easier to reproduce and assess. An illustrative example shows how TURTLE (Terse RDF Triple Language) can be used as a human readable, but also semantically-aware, equivalent to GenBank/EMBL files. Conclusions The power of this approach lies in its ability to assemble annotation data from multiple databases across multiple locations into a representation that is understandable to researchers. In this way, all researchers, experimental and computational, will more easily understand the informatics processes constructing genome annotation and ultimately be able to help improve the systems that produce them.« less

IMG/M: integrated genome and metagenome comparative data analysis system

DOE PAGES

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; ...

2016-10-13

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support formore » examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review(ER) companion system (IMG/M ER: https://img.jgi.doe.gov/ mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.« less

IMG/M: integrated genome and metagenome comparative data analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support formore » examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review(ER) companion system (IMG/M ER: https://img.jgi.doe.gov/ mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.« less

IMG/M: integrated genome and metagenome comparative data analysis system

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Palaniappan, Krishna; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Andersen, Evan; Huntemann, Marcel; Varghese, Neha; Hadjithomas, Michalis; Tennessen, Kristin; Nielsen, Torben; Ivanova, Natalia N.; Kyrpides, Nikos C.

2017-01-01

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system. PMID:27738135

Integrating grant-funded research into the undergraduate biology curriculum using IMG-ACT.

PubMed

Ditty, Jayna L; Williams, Kayla M; Keller, Megan M; Chen, Grischa Y; Liu, Xianxian; Parales, Rebecca E

2013-01-01

It has become clear in current scientific pedagogy that the emersion of students in the scientific process in terms of designing, implementing, and analyzing experiments is imperative for their education; as such, it has been our goal to model this active learning process in the classroom and laboratory in the context of a genuine scientific question. Toward this objective, the National Science Foundation funded a collaborative research grant between a primarily undergraduate institution and a research-intensive institution to study the chemotactic responses of the bacterium Pseudomonas putida F1. As part of the project, a new Bioinformatics course was developed in which undergraduates annotate relevant regions of the P. putida F1 genome using Integrated Microbial Genomes Annotation Collaboration Toolkit, a bioinformatics interface specifically developed for undergraduate programs by the Department of Energy Joint Genome Institute. Based on annotations of putative chemotaxis genes in P. putida F1 and comparative genomics studies, undergraduate students from both institutions developed functional genomics research projects that evolved from the annotations. The purpose of this study is to describe the nature of the NSF grant, the development of the Bioinformatics lecture and wet laboratory course, and how undergraduate student involvement in the project that was initiated in the classroom has served as a springboard for independent undergraduate research projects. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

Gramene 2013: comparative plant genomics resources.

PubMed

Monaco, Marcela K; Stein, Joshua; Naithani, Sushma; Wei, Sharon; Dharmawardhana, Palitha; Kumari, Sunita; Amarasinghe, Vindhya; Youens-Clark, Ken; Thomason, James; Preece, Justin; Pasternak, Shiran; Olson, Andrew; Jiao, Yinping; Lu, Zhenyuan; Bolser, Dan; Kerhornou, Arnaud; Staines, Dan; Walts, Brandon; Wu, Guanming; D'Eustachio, Peter; Haw, Robin; Croft, David; Kersey, Paul J; Stein, Lincoln; Jaiswal, Pankaj; Ware, Doreen

2014-01-01

Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.

Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan.

PubMed

Standley, Daron M; Toh, Hiroyuki; Nakamura, Haruki

2008-09-01

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized. 2008 Wiley-Liss, Inc.

The challenge of annotating protein sequences: The tale of eight domains of unknown function in Pfam.

PubMed

Goonesekere, Nalin C W; Shipely, Krysten; O'Connor, Kevin

2010-06-01

The Pfam database is an important tool in genome annotation, since it provides a collection of curated protein families. However, a subset of these families, known as domains of unknown function (DUFs), remains poorly characterized. We have related sequences from DUF404, DUF407, DUF482, DUF608, DUF810, DUF853, DUF976 and DUF1111 to homologs in PDB, within the midnight zone (9-20%) of sequence identity. These relationships were extended to provide functional annotation by sequence analysis and model building. Also described are examples of residue plasticity within enzyme active sites, and change of function within homologous sequences of a DUF. Copyright 2010 Elsevier Ltd. All rights reserved.

OGRO: The Overview of functionally characterized Genes in Rice online database.

PubMed

Yamamoto, Eiji; Yonemaru, Jun-Ichi; Yamamoto, Toshio; Yano, Masahiro

2012-12-01

The high-quality sequence information and rich bioinformatics tools available for rice have contributed to remarkable advances in functional genomics. To facilitate the application of gene function information to the study of natural variation in rice, we comprehensively searched for articles related to rice functional genomics and extracted information on functionally characterized genes. As of 31 March 2012, 702 functionally characterized genes were annotated. This number represents about 1.6% of the predicted loci in the Rice Annotation Project Database. The compiled gene information is organized to facilitate direct comparisons with quantitative trait locus (QTL) information in the Q-TARO database. Comparison of genomic locations between functionally characterized genes and the QTLs revealed that QTL clusters were often co-localized with high-density gene regions, and that the genes associated with the QTLs in these clusters were different genes, suggesting that these QTL clusters are likely to be explained by tightly linked but distinct genes. Information on the functionally characterized genes compiled during this study is now available in the O verview of Functionally Characterized G enes in R ice O nline database (OGRO) on the Q-TARO website ( http://qtaro.abr.affrc.go.jp/ogro ). The database has two interfaces: a table containing gene information, and a genome viewer that allows users to compare the locations of QTLs and functionally characterized genes. OGRO on Q-TARO will facilitate a candidate-gene approach to identifying the genes responsible for QTLs. Because the QTL descriptions in Q-TARO contain information on agronomic traits, such comparisons will also facilitate the annotation of functionally characterized genes in terms of their effects on traits important for rice breeding. The increasing amount of information on rice gene function being generated from mutant panels and other types of studies will make the OGRO database even more valuable in the future.

A guide to best practices for Gene Ontology (GO) manual annotation

PubMed Central

Balakrishnan, Rama; Harris, Midori A.; Huntley, Rachael; Van Auken, Kimberly; Cherry, J. Michael

2013-01-01

The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374 000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all. Database URL: http://www.geneontology.org PMID:23842463

Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database.

PubMed

Carver, Tim; Berriman, Matthew; Tivey, Adrian; Patel, Chinmay; Böhme, Ulrike; Barrell, Barclay G; Parkhill, Julian; Rajandream, Marie-Adèle

2008-12-01

Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/

Recognition of Protein-coding Genes Based on Z-curve Algorithms

PubMed Central

-Biao Guo, Feng; Lin, Yan; -Ling Chen, Ling

2014-01-01

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation. PMID:24822027

Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida

PubMed Central

Pirooznia, Mehdi; Gong, Ping; Guan, Xin; Inouye, Laura S; Yang, Kuan; Perkins, Edward J; Deng, Youping

2007-01-01

Background Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR. Results A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone sequences after cleaning. Clustering analysis yielded 2231 unique sequences including 448 contigs (from 1361 ESTs) and 1783 singletons. Comparative genomic analysis showed that 743 or 33% of the unique sequences shared high similarity with existing genes in the GenBank nr database. Provisional function annotation assigned 830 Gene Ontology terms to 517 unique sequences based on their homology with the annotated genomes of four model organisms Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, and Caenorhabditis elegans. Seven percent of the unique sequences were further mapped to 99 Kyoto Encyclopedia of Genes and Genomes pathways based on their matching Enzyme Commission numbers. All the information is stored and retrievable at a highly performed, web-based and user-friendly relational database called EST model database or ESTMD version 2. Conclusion The ESTMD containing the sequence and annotation information of 4032 E. fetida ESTs is publicly accessible at . PMID:18047730

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

PubMed

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

Complete nucleotide sequence and annotation of the temperate corynephage ϕ16 genome.

PubMed

Lobanova, Juliya S; Gak, Evgueni R; Andreeva, Irina G; Rybak, Konstantin V; Krylov, Alexander A; Mashko, Sergey V

2017-08-01

The complete genome of ϕ16, a temperate corynephage from Corynebacterium glutamicum ATCC 21792, was sequenced and annotated (GenBank: KY250482). The electron microscopy study of ϕ16 virion confirmed that it belongs to the family Siphoviridae. The ϕ16 genome consists of a linear double-stranded DNA molecule of 58,200 bp (G+C = 52.2%) with protruding cohesive 3'-ends of 14 nt. Four major structural proteins were separated by SDS-PAGE and identified by peptide mass fingerprinting technique. Using bioinformatics analysis, 101 putative ORFs and 5 tRNA genes were predicted. Only 27 putative gene products could be assigned to known biological functions. The ϕ16 genome was divided into functional modules. Seven putative promoters and eight putative unidirectional intrinsic terminators were predicted. One site of putative «-1» programmed ribosomal frameshifting was proposed in the phage tail assembly genome region. C. glutamicum genetic tools could be broadened by exploiting the known integrase gene (gp33) and the newly identified excisionase gene (gp47), participating in site-specific recombination between ϕ16-attP/attB.

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

Anopheles gambiae genome reannotation through synthesis of ab initio and comparative gene prediction algorithms

PubMed Central

Li, Jun; Riehle, Michelle M; Zhang, Yan; Xu, Jiannong; Oduol, Frederick; Gomez, Shawn M; Eiglmeier, Karin; Ueberheide, Beatrix M; Shabanowitz, Jeffrey; Hunt, Donald F; Ribeiro, José MC; Vernick, Kenneth D

2006-01-01

Background Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. Results We reannotate the A. gambiae genome by synthesizing comparative and ab initio sets of predicted coding sequences (CDSs) into a single set using an exon-gene-union algorithm followed by an open-reading-frame-selection algorithm. The reannotation predicts 20,970 CDSs supported by at least two lines of evidence, and it lowers the proportion of CDSs lacking start and/or stop codons to only approximately 4%. The reannotated CDS set includes a set of 4,681 novel CDSs not represented in the Ensembl annotation but with EST support, and another set of 4,031 Ensembl-supported genes that undergo major structural and, therefore, probably functional changes in the reannotated set. The quality and accuracy of the reannotation was assessed by comparison with end sequences from 20,249 full-length cDNA clones, and evaluation of mass spectrometry peptide hit rates from an A. gambiae shotgun proteomic dataset confirms that the reannotated CDSs offer a high quality protein database for proteomics. We provide a functional proteomics annotation, ReAnoXcel, obtained by analysis of the new CDSs through the AnoXcel pipeline, which allows functional comparisons of the CDS sets within the same bioinformatic platform. CDS data are available for download. Conclusion Comprehensive A. gambiae genome reannotation is achieved through a combination of comparative and ab initio gene prediction algorithms. PMID:16569258

Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals.

PubMed

Taylor, Jeremy F; Whitacre, Lynsey K; Hoff, Jesse L; Tizioto, Polyana C; Kim, JaeWoo; Decker, Jared E; Schnabel, Robert D

2016-08-17

Decreasing sequencing costs and development of new protocols for characterizing global methylation, gene expression patterns and regulatory regions have stimulated the generation of large livestock datasets. Here, we discuss experiences in the analysis of whole-genome and transcriptome sequence data. We analyzed whole-genome sequence (WGS) data from 132 individuals from five canid species (Canis familiaris, C. latrans, C. dingo, C. aureus and C. lupus) and 61 breeds, three bison (Bison bison), 64 water buffalo (Bubalus bubalis) and 297 bovines from 17 breeds. By individual, data vary in extent of reference genome depth of coverage from 4.9X to 64.0X. We have also analyzed RNA-seq data for 580 samples representing 159 Bos taurus and Rattus norvegicus animals and 98 tissues. By aligning reads to a reference assembly and calling variants, we assessed effects of average depth of coverage on the actual coverage and on the number of called variants. We examined the identity of unmapped reads by assembling them and querying produced contigs against the non-redundant nucleic acids database. By imputing high-density single nucleotide polymorphism data on 4010 US registered Angus animals to WGS using Run4 of the 1000 Bull Genomes Project and assessing the accuracy of imputation, we identified misassembled reference sequence regions. We estimate that a 24X depth of coverage is required to achieve 99.5 % coverage of the reference assembly and identify 95 % of the variants within an individual's genome. Genomes sequenced to low average coverage (e.g., <10X) may fail to cover 10 % of the reference genome and identify <75 % of variants. About 10 % of genomic DNA or transcriptome sequence reads fail to align to the reference assembly. These reads include loci missing from the reference assembly and misassembled genes and interesting symbionts, commensal and pathogenic organisms. Assembly errors and a lack of annotation of functional elements significantly limit the utility of the current draft livestock reference assemblies. The Functional Annotation of Animal Genomes initiative seeks to annotate functional elements, while a 70X Pac-Bio assembly for cow is underway and may result in a significantly improved reference assembly.

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.

PubMed

Fang, Hai; Knezevic, Bogdan; Burnham, Katie L; Knight, Julian C

2016-12-13

Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .

Incidence of genome structure, DNA asymmetry, and cell physiology on T-DNA integration in chromosomes of the phytopathogenic fungus Leptosphaeria maculans.

PubMed

Bourras, Salim; Meyer, Michel; Grandaubert, Jonathan; Lapalu, Nicolas; Fudal, Isabelle; Linglin, Juliette; Ollivier, Benedicte; Blaise, Françoise; Balesdent, Marie-Hélène; Rouxel, Thierry

2012-08-01

The ever-increasing generation of sequence data is accompanied by unsatisfactory functional annotation, and complex genomes, such as those of plants and filamentous fungi, show a large number of genes with no predicted or known function. For functional annotation of unknown or hypothetical genes, the production of collections of mutants using Agrobacterium tumefaciens-mediated transformation (ATMT) associated with genotyping and phenotyping has gained wide acceptance. ATMT is also widely used to identify pathogenicity determinants in pathogenic fungi. A systematic analysis of T-DNA borders was performed in an ATMT-mutagenized collection of the phytopathogenic fungus Leptosphaeria maculans to evaluate the features of T-DNA integration in its particular transposable element-rich compartmentalized genome. A total of 318 T-DNA tags were recovered and analyzed for biases in chromosome and genic compartments, existence of CG/AT skews at the insertion site, and occurrence of microhomologies between the T-DNA left border (LB) and the target sequence. Functional annotation of targeted genes was done using the Gene Ontology annotation. The T-DNA integration mainly targeted gene-rich, transcriptionally active regions, and it favored biological processes consistent with the physiological status of a germinating spore. T-DNA integration was strongly biased toward regulatory regions, and mainly promoters. Consistent with the T-DNA intranuclear-targeting model, the density of T-DNA insertion correlated with CG skew near the transcription initiation site. The existence of microhomologies between promoter sequences and the T-DNA LB flanking sequence was also consistent with T-DNA integration to host DNA mediated by homologous recombination based on the microhomology-mediated end-joining pathway.

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

PubMed Central

Aubry, Marc; Monnier, Annabelle; Chicault, Celine; de Tayrac, Marie; Galibert, Marie-Dominique; Burgun, Anita; Mosser, Jean

2006-01-01

Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions. PMID:16674810

Genome scaffolding and annotation for the pathogen vector Ixodes ricinus by ultra-long single molecule sequencing.

PubMed

Cramaro, Wibke J; Hunewald, Oliver E; Bell-Sakyi, Lesley; Muller, Claude P

2017-02-08

Global warming and other ecological changes have facilitated the expansion of Ixodes ricinus tick populations. Ixodes ricinus is the most important carrier of vector-borne pathogens in Europe, transmitting viruses, protozoa and bacteria, in particular Borrelia burgdorferi (sensu lato), the causative agent of Lyme borreliosis, the most prevalent vector-borne disease in humans in the Northern hemisphere. To faster control this disease vector, a better understanding of the I. ricinus tick is necessary. To facilitate such studies, we recently published the first reference genome of this highly prevalent pathogen vector. Here, we further extend these studies by scaffolding and annotating the first reference genome by using ultra-long sequencing reads from third generation single molecule sequencing. In addition, we present the first genome size estimation for I. ricinus ticks and the embryo-derived cell line IRE/CTVM19. 235,953 contigs were integrated into 204,904 scaffolds, extending the currently known genome lengths by more than 30% from 393 to 516 Mb and the N50 contig value by 87% from 1643 bp to a N50 scaffold value of 3067 bp. In addition, 25,263 sequences were annotated by comparison to the tick's North American relative Ixodes scapularis. After (conserved) hypothetical proteins, zinc finger proteins, secreted proteins and P450 coding proteins were the most prevalent protein categories annotated. Interestingly, more than 50% of the amino acid sequences matching the homology threshold had 95-100% identity to the corresponding I. scapularis gene models. The sequence information was complemented by the first genome size estimation for this species. Flow cytometry-based genome size analysis revealed a haploid genome size of 2.65Gb for I. ricinus ticks and 3.80 Gb for the cell line. We present a first draft sequence map of the I. ricinus genome based on a PacBio-Illumina assembly. The I. ricinus genome was shown to be 26% (500 Mb) larger than the genome of its American relative I. scapularis. Based on the genome size of 2.65 Gb we estimated that we covered about 67% of the non-repetitive sequences. Genome annotation will facilitate screening for specific molecular pathways in I. ricinus cells and provides an overview of characteristics and functions.

Analysis of the Genome and Chromium Metabolism-Related Genes of Serratia sp. S2.

PubMed

Dong, Lanlan; Zhou, Simin; He, Yuan; Jia, Yan; Bai, Qunhua; Deng, Peng; Gao, Jieying; Li, Yingli; Xiao, Hong

2018-05-01

This study is to investigate the genome sequence of Serratia sp. S2. The genomic DNA of Serratia sp. S2 was extracted and the sequencing library was constructed. The sequencing was carried out by Illumina 2000 and complete genomic sequences were obtained. Gene function annotation and bioinformatics analysis were performed by comparing with the known databases. The genome size of Serratia sp. S2 was 5,604,115 bp and the G+C content was 57.61%. There were 5373 protein coding genes, and 3732, 3614, and 3942 genes were respectively annotated into the GO, KEGG, and COG databases. There were 12 genes related to chromium metabolism in the Serratia sp. S2 genome. The whole genome sequence of Serratia sp. S2 is submitted to the GenBank database with gene accession number of LNRP00000000. Our findings may provide theoretical basis for the subsequent development of new biotechnology to repair environmental chromium pollution.

Micro-Plasticity of Genomes As Illustrated by the Evolution of Glutathione Transferases in 12 Drosophila Species

PubMed Central

Saisawang, Chonticha; Ketterman, Albert J.

2014-01-01

Glutathione transferases (GST) are an ancient superfamily comprising a large number of paralogous proteins in a single organism. This multiplicity of GSTs has allowed the copies to diverge for neofunctionalization with proposed roles ranging from detoxication and oxidative stress response to involvement in signal transduction cascades. We performed a comparative genomic analysis using FlyBase annotations and Drosophila melanogaster GST sequences as templates to further annotate the GST orthologs in the 12 Drosophila sequenced genomes. We found that GST genes in the Drosophila subgenera have undergone repeated local duplications followed by transposition, inversion, and micro-rearrangements of these copies. The colinearity and orientations of the orthologous GST genes appear to be unique in many of the species which suggests that genomic rearrangement events have occurred multiple times during speciation. The high micro-plasticity of the genomes appears to have a functional contribution utilized for evolution of this gene family. PMID:25310450

RGmatch: matching genomic regions to proximal genes in omics data integration.

PubMed

Furió-Tarí, Pedro; Conesa, Ana; Tarazona, Sonia

2016-11-22

The integrative analysis of multiple genomics data often requires that genome coordinates-based signals have to be associated with proximal genes. The relative location of a genomic region with respect to the gene (gene area) is important for functional data interpretation; hence algorithms that match regions to genes should be able to deliver insight into this information. In this work we review the tools that are publicly available for making region-to-gene associations. We also present a novel method, RGmatch, a flexible and easy-to-use Python tool that computes associations either at the gene, transcript, or exon level, applying a set of rules to annotate each region-gene association with the region location within the gene. RGmatch can be applied to any organism as long as genome annotation is available. Furthermore, we qualitatively and quantitatively compare RGmatch to other tools. RGmatch simplifies the association of a genomic region with its closest gene. At the same time, it is a powerful tool because the rules used to annotate these associations are very easy to modify according to the researcher's specific interests. Some important differences between RGmatch and other similar tools already in existence are RGmatch's flexibility, its wide range of user options, compatibility with any annotatable organism, and its comprehensive and user-friendly output.

Draft genome of the red harvester ant Pogonomyrmex barbatus.

PubMed

Smith, Chris R; Smith, Christopher D; Robertson, Hugh M; Helmkampf, Martin; Zimin, Aleksey; Yandell, Mark; Holt, Carson; Hu, Hao; Abouheif, Ehab; Benton, Richard; Cash, Elizabeth; Croset, Vincent; Currie, Cameron R; Elhaik, Eran; Elsik, Christine G; Favé, Marie-Julie; Fernandes, Vilaiwan; Gibson, Joshua D; Graur, Dan; Gronenberg, Wulfila; Grubbs, Kirk J; Hagen, Darren E; Viniegra, Ana Sofia Ibarraran; Johnson, Brian R; Johnson, Reed M; Khila, Abderrahman; Kim, Jay W; Mathis, Kaitlyn A; Munoz-Torres, Monica C; Murphy, Marguerite C; Mustard, Julie A; Nakamura, Rin; Niehuis, Oliver; Nigam, Surabhi; Overson, Rick P; Placek, Jennifer E; Rajakumar, Rajendhran; Reese, Justin T; Suen, Garret; Tao, Shu; Torres, Candice W; Tsutsui, Neil D; Viljakainen, Lumi; Wolschin, Florian; Gadau, Jürgen

2011-04-05

We report the draft genome sequence of the red harvester ant, Pogonomyrmex barbatus. The genome was sequenced using 454 pyrosequencing, and the current assembly and annotation were completed in less than 1 y. Analyses of conserved gene groups (more than 1,200 manually annotated genes to date) suggest a high-quality assembly and annotation comparable to recently sequenced insect genomes using Sanger sequencing. The red harvester ant is a model for studying reproductive division of labor, phenotypic plasticity, and sociogenomics. Although the genome of P. barbatus is similar to other sequenced hymenopterans (Apis mellifera and Nasonia vitripennis) in GC content and compositional organization, and possesses a complete CpG methylation toolkit, its predicted genomic CpG content differs markedly from the other hymenopterans. Gene networks involved in generating key differences between the queen and worker castes (e.g., wings and ovaries) show signatures of increased methylation and suggest that ants and bees may have independently co-opted the same gene regulatory mechanisms for reproductive division of labor. Gene family expansions (e.g., 344 functional odorant receptors) and pseudogene accumulation in chemoreception and P450 genes compared with A. mellifera and N. vitripennis are consistent with major life-history changes during the adaptive radiation of Pogonomyrmex spp., perhaps in parallel with the development of the North American deserts.

GenomeGraphs: integrated genomic data visualization with R.

PubMed

Durinck, Steffen; Bullard, James; Spellman, Paul T; Dudoit, Sandrine

2009-01-06

Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses. We developed GenomeGraphs, as an add-on software package for the statistical programming environment R, to facilitate integrated visualization of genomic datasets. GenomeGraphs uses the biomaRt package to perform on-line annotation queries to Ensembl and translates these to gene/transcript structures in viewports of the grid graphics package. This allows genomic annotation to be plotted together with experimental data. GenomeGraphs can also be used to plot custom annotation tracks in combination with different experimental data types together in one plot using the same genomic coordinate system. GenomeGraphs is a flexible and extensible software package which can be used to visualize a multitude of genomic datasets within the statistical programming environment R.

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

PubMed

McNeil, Leslie Klis; Reich, Claudia; Aziz, Ramy K; Bartels, Daniela; Cohoon, Matthew; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Hwang, Kaitlyn; Kubal, Michael; Margaryan, Gohar Rem; Meyer, Folker; Mihalo, William; Olsen, Gary J; Olson, Robert; Osterman, Andrei; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Rodionov, Dmitry A; Shi, Xinghua; Vassieva, Olga; Vonstein, Veronika; Zagnitko, Olga; Xia, Fangfang; Zinner, Jenifer; Overbeek, Ross; Stevens, Rick

2007-01-01

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.

A new approach for annotation of transposable elements using small RNA mapping

PubMed Central

El Baidouri, Moaine; Kim, Kyung Do; Abernathy, Brian; Arikit, Siwaret; Maumus, Florian; Panaud, Olivier; Meyers, Blake C.; Jackson, Scott A.

2015-01-01

Transposable elements (TEs) are mobile genomic DNA sequences found in most organisms. They so densely populate the genomes of many eukaryotic species that they are often the major constituents. With the rapid generation of many plant genome sequencing projects over the past few decades, there is an urgent need for improved TE annotation as a prerequisite for genome-wide studies. Analogous to the use of RNA-seq for gene annotation, we propose a new method for de novo TE annotation that uses as a guide 24 nt-siRNAs that are a part of TE silencing pathways. We use this new approach, called TASR (for Transposon Annotation using Small RNAs), for de novo annotation of TEs in Arabidopsis, rice and soybean and demonstrate that this strategy can be successfully applied for de novo TE annotation in plants. Executable PERL is available for download from: http://tasr-pipeline.sourceforge.net/ PMID:25813049

SOBA: sequence ontology bioinformatics analysis.

PubMed

Moore, Barry; Fan, Guozhen; Eilbeck, Karen

2010-07-01

The advent of cheaper, faster sequencing technologies has pushed the task of sequence annotation from the exclusive domain of large-scale multi-national sequencing projects to that of research laboratories and small consortia. The bioinformatics burden placed on these laboratories, some with very little programming experience can be daunting. Fortunately, there exist software libraries and pipelines designed with these groups in mind, to ease the transition from an assembled genome to an annotated and accessible genome resource. We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

Improved Annotation of 3′ Untranslated Regions and Complex Loci by Combination of Strand-Specific Direct RNA Sequencing, RNA-Seq and ESTs

PubMed Central

Song, Junfang; Duc, Céline; Storey, Kate G.; McLean, W. H. Irwin; Brown, Sara J.; Simpson, Gordon G.; Barton, Geoffrey J.

2014-01-01

The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3′ untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3′ polyadenylation sites to within +/− 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3′ UTR re-annotation (including extension of one 3′ UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data. PMID:24722185

The proteome: structure, function and evolution

PubMed Central

Fleming, Keiran; Kelley, Lawrence A; Islam, Suhail A; MacCallum, Robert M; Muller, Arne; Pazos, Florencio; Sternberg, Michael J.E

2006-01-01

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family. PMID:16524832

A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

PubMed

Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A

2014-10-12

BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.

Resolving the problem of multiple accessions of the same transcript deposited across various public databases.

PubMed

Weirick, Tyler; John, David; Uchida, Shizuka

2017-03-01

Maintaining the consistency of genomic annotations is an increasingly complex task because of the iterative and dynamic nature of assembly and annotation, growing numbers of biological databases and insufficient integration of annotations across databases. As information exchange among databases is poor, a 'novel' sequence from one reference annotation could be annotated in another. Furthermore, relationships to nearby or overlapping annotated transcripts are even more complicated when using different genome assemblies. To better understand these problems, we surveyed current and previous versions of genomic assemblies and annotations across a number of public databases containing long noncoding RNA. We identified numerous discrepancies of transcripts regarding their genomic locations, transcript lengths and identifiers. Further investigation showed that the positional differences between reference annotations of essentially the same transcript could lead to differences in its measured expression at the RNA level. To aid in resolving these problems, we present the algorithm 'Universal Genomic Accession Hash (UGAHash)' and created an open source web tool to encourage the usage of the UGAHash algorithm. The UGAHash web tool (http://ugahash.uni-frankfurt.de) can be accessed freely without registration. The web tool allows researchers to generate Universal Genomic Accessions for genomic features or to explore annotations deposited in the public databases of the past and present versions. We anticipate that the UGAHash web tool will be a valuable tool to check for the existence of transcripts before judging the newly discovered transcripts as novel. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

No wisdom in the crowd: genome annotation in the era of big data - current status and future prospects.

PubMed

Danchin, Antoine; Ouzounis, Christos; Tokuyasu, Taku; Zucker, Jean-Daniel

2018-07-01

Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in biological research and reflects the nature of biology itself. Annotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. By combining deduction, induction and abduction, investigators can generate hypotheses when accurate knowledge is extracted from model databases. A key stance is to depart from 'the sequence tells the structure tells the function' fallacy, placing function first. We illustrate our approach with examples of critical or unexpected pathways, using MicroScope to demonstrate how tools can be implemented following the principles we advocate. We end with a challenge to the reader. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales

PubMed Central

Makarova, Kira S.; Wolf, Yuri I.; Koonin, Eugene V.

2015-01-01

With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for orthology identification combined with extensive manual curation, including incorporation of the results of several completed and ongoing research projects in archaeal genomics. A new level of classification is introduced, superclusters that unit two or more arCOGs and more completely reflect gene family evolution than individual, disconnected arCOGs. Assessment of the current archaeal genome annotation in public databases indicates that consistent use of arCOGs can significantly improve the annotation quality. In addition to their utility for genome annotation, arCOGs also are a platform for phylogenomic analysis. We explore this aspect of arCOGs by performing a phylogenomic study of the Thermococci that are traditionally viewed as the basal branch of the Euryarchaeota. The results of phylogenomic analysis that involved both comparison of multiple phylogenetic trees and a search for putative derived shared characters by using phyletic patterns extracted from the arCOGs reveal a likely evolutionary relationship between the Thermococci, Methanococci, and Methanobacteria. The arCOGs are expected to be instrumental for a comprehensive phylogenomic study of the archaea. PMID:25764277

The integrated web service and genome database for agricultural plants with biotechnology information.

PubMed

Kim, Changkug; Park, Dongsuk; Seol, Youngjoo; Hahn, Jangho

2011-01-01

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a Web based relational database for agricultural plants with biotechnology information. The NABIC has concentrated on functional genomics of major agricultural plants, building an integrated biotechnology database for agro-biotech information that focuses on genomics of major agricultural resources. This genome database provides annotated genome information from 1,039,823 records mapped to rice, Arabidopsis, and Chinese cabbage.

The Yak genome database: an integrative database for studying yak biology and high-altitude adaption

PubMed Central

2012-01-01

Background The yak (Bos grunniens) is a long-haired bovine that lives at high altitudes and is an important source of milk, meat, fiber and fuel. The recent sequencing, assembly and annotation of its genome are expected to further our understanding of the means by which it has adapted to life at high altitudes and its ecologically important traits. Description The Yak Genome Database (YGD) is an internet-based resource that provides access to genomic sequence data and predicted functional information concerning the genes and proteins of Bos grunniens. The curated data stored in the YGD includes genome sequences, predicted genes and associated annotations, non-coding RNA sequences, transposable elements, single nucleotide variants, and three-way whole-genome alignments between human, cattle and yak. YGD offers useful searching and data mining tools, including the ability to search for genes by name or using function keywords as well as GBrowse genome browsers and/or BLAST servers, which can be used to visualize genome regions and identify similar sequences. Sequence data from the YGD can also be downloaded to perform local searches. Conclusions A new yak genome database (YGD) has been developed to facilitate studies on high-altitude adaption and bovine genomics. The database will be continuously updated to incorporate new information such as transcriptome data and population resequencing data. The YGD can be accessed at http://me.lzu.edu.cn/yak. PMID:23134687

Transcriptome characterization for genome annotation and functional genomics in Theobroma cacao

USDA-ARS?s Scientific Manuscript database

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...

Draft genome of the gayal, Bos frontalis

PubMed Central

Wang, Ming-Shan; Zeng, Yan; Wang, Xiao; Nie, Wen-Hui; Wang, Jin-Huan; Su, Wei-Ting; Xiong, Zi-Jun; Wang, Sheng; Qu, Kai-Xing; Yan, Shou-Qing; Yang, Min-Min; Wang, Wen; Dong, Yang; Zhang, Ya-Ping

2017-01-01

Abstract Gayal (Bos frontalis), also known as mithan or mithun, is a large endangered semi-domesticated bovine that has a limited geographical distribution in the hill-forests of China, Northeast India, Bangladesh, Myanmar, and Bhutan. Many questions about the gayal such as its origin, population history, and genetic basis of local adaptation remain largely unresolved. De novo sequencing and assembly of the whole gayal genome provides an opportunity to address these issues. We report a high-depth sequencing, de novo assembly, and annotation of a female Chinese gayal genome. Based on the Illumina genomic sequencing platform, we have generated 350.38 Gb of raw data from 16 different insert-size libraries. A total of 276.86 Gb of clean data is retained after quality control. The assembled genome is about 2.85 Gb with scaffold and contig N50 sizes of 2.74 Mb and 14.41 kb, respectively. Repetitive elements account for 48.13% of the genome. Gene annotation has yielded 26 667 protein-coding genes, of which 97.18% have been functionally annotated. BUSCO assessment shows that our assembly captures 93% (3183 of 4104) of the core eukaryotic genes and 83.1% of vertebrate universal single-copy orthologs. We provide the first comprehensive de novo genome of the gayal. This genetic resource is integral for investigating the origin of the gayal and performing comparative genomic studies to improve understanding of the speciation and divergence of bovine species. The assembled genome could be used as reference in future population genetic studies of gayal. PMID:29048483

A computational genomics pipeline for prokaryotic sequencing projects.

PubMed

Kislyuk, Andrey O; Katz, Lee S; Agrawal, Sonia; Hagen, Matthew S; Conley, Andrew B; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C; Sammons, Scott A; Govil, Dhwani; Mair, Raydel D; Tatti, Kathleen M; Tondella, Maria L; Harcourt, Brian H; Mayer, Leonard W; Jordan, I King

2010-08-01

New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.

Integrated genome browser: visual analytics platform for genomics.

PubMed

Freese, Nowlan H; Norris, David C; Loraine, Ann E

2016-07-15

Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB's ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. IGB is open source and is freely available from http://bioviz.org/igb aloraine@uncc.edu. © The Author 2016. Published by Oxford University Press.

Assembly, Annotation, and Analysis of Multiple Mycorrhizal Fungal Genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Initiative Consortium, Mycorrhizal Genomics; Kuo, Alan; Grigoriev, Igor

Mycorrhizal fungi play critical roles in host plant health, soil community structure and chemistry, and carbon and nutrient cycling, all areas of intense interest to the US Dept. of Energy (DOE) Joint Genome Institute (JGI). To this end we are building on our earlier sequencing of the Laccaria bicolor genome by partnering with INRA-Nancy and the mycorrhizal research community in the MGI to sequence and analyze dozens of mycorrhizal genomes of all Basidiomycota and Ascomycota orders and multiple ecological types (ericoid, orchid, and ectomycorrhizal). JGI has developed and deployed high-throughput sequencing techniques, and Assembly, RNASeq, and Annotation Pipelines. In 2012more » alone we sequenced, assembled, and annotated 12 draft or improved genomes of mycorrhizae, and predicted ~;;232831 genes and ~;;15011 multigene families, All of this data is publicly available on JGI MycoCosm (http://jgi.doe.gov/fungi/), which provides access to both the genome data and tools with which to analyze the data. Preliminary comparisons of the current total of 14 public mycorrhizal genomes suggest that 1) short secreted proteins potentially involved in symbiosis are more enriched in some orders than in others amongst the mycorrhizal Agaricomycetes, 2) there are wide ranges of numbers of genes involved in certain functional categories, such as signal transduction and post-translational modification, and 3) novel gene families are specific to some ecological types.« less

Comprehensive phylogenetic analysis of bacterial reverse transcriptases.

PubMed

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology.

Comprehensive Phylogenetic Analysis of Bacterial Reverse Transcriptases

PubMed Central

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology. PMID:25423096

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

dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts

PubMed Central

Vincent, Jonathan; Dai, Zhanwu; Ravel, Catherine; Choulet, Frédéric; Mouzeyar, Said; Bouzidi, M. Fouad; Agier, Marie; Martre, Pierre

2013-01-01

The functional annotation of genes based on sequence homology with genes from model species genomes is time-consuming because it is necessary to mine several unrelated databases. The aim of the present work was to develop a functional annotation database for common wheat Triticum aestivum (L.). The database, named dbWFA, is based on the reference NCBI UniGene set, an expressed gene catalogue built by expressed sequence tag clustering, and on full-length coding sequences retrieved from the TriFLDB database. Information from good-quality heterogeneous sources, including annotations for model plant species Arabidopsis thaliana (L.) Heynh. and Oryza sativa L., was gathered and linked to T. aestivum sequences through BLAST-based homology searches. Even though the complexity of the transcriptome cannot yet be fully appreciated, we developed a tool to easily and promptly obtain information from multiple functional annotation systems (Gene Ontology, MapMan bin codes, MIPS Functional Categories, PlantCyc pathway reactions and TAIR gene families). The use of dbWFA is illustrated here with several query examples. We were able to assign a putative function to 45% of the UniGenes and 81% of the full-length coding sequences from TriFLDB. Moreover, comparison of the annotation of the whole T. aestivum UniGene set along with curated annotations of the two model species assessed the accuracy of the annotation provided by dbWFA. To further illustrate the use of dbWFA, genes specifically expressed during the early cell division or late storage polymer accumulation phases of T. aestivum grain development were identified using a clustering analysis and then annotated using dbWFA. The annotation of these two sets of genes was consistent with previous analyses of T. aestivum grain transcriptomes and proteomes. Database URL: urgi.versailles.inra.fr/dbWFA/ PMID:23660284

RNASeq-based genome annotation and identification of long-noncoding RNAs in the grapevine cultivar 'Riesling'

USDA-ARS?s Scientific Manuscript database

The technological advances of RNA-seq and de novo transcriptome assembly have enabled genome annotation and transcriptome profiling in heterozygous species. This is a promising approach to improving the annotation of the reference genome sequence of grapevine (Vitis vinifera L.), a species of high-l...

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists

PubMed Central

Wiley, Laura K.; Sivley, R. Michael; Bush, William S.

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist PMID:23894185

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

PubMed

Wiley, Laura K; Sivley, R Michael; Bush, William S

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

The language of gene ontology: a Zipf's law analysis.

PubMed

Kalankesh, Leila Ranandeh; Stevens, Robert; Brass, Andy

2012-06-07

Most major genome projects and sequence databases provide a GO annotation of their data, either automatically or through human annotators, creating a large corpus of data written in the language of GO. Texts written in natural language show a statistical power law behaviour, Zipf's law, the exponent of which can provide useful information on the nature of the language being used. We have therefore explored the hypothesis that collections of GO annotations will show similar statistical behaviours to natural language. Annotations from the Gene Ontology Annotation project were found to follow Zipf's law. Surprisingly, the measured power law exponents were consistently different between annotation captured using the three GO sub-ontologies in the corpora (function, process and component). On filtering the corpora using GO evidence codes we found that the value of the measured power law exponent responded in a predictable way as a function of the evidence codes used to support the annotation. Techniques from computational linguistics can provide new insights into the annotation process. GO annotations show similar statistical behaviours to those seen in natural language with measured exponents that provide a signal which correlates with the nature of the evidence codes used to support the annotations, suggesting that the measured exponent might provide a signal regarding the information content of the annotation.

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 phylogeny for the entire currently known VvTPS gene family. PMID:20964856

Finding functional features in Saccharomyces genomes by phylogenetic footprinting.

PubMed

Cliften, Paul; Sudarsanam, Priya; Desikan, Ashwin; Fulton, Lucinda; Fulton, Bob; Majors, John; Waterston, Robert; Cohen, Barak A; Johnston, Mark

2003-07-04

The sifting and winnowing of DNA sequence that occur during evolution cause nonfunctional sequences to diverge, leaving phylogenetic footprints of functional sequence elements in comparisons of genome sequences. We searched for such footprints among the genome sequences of six Saccharomyces species and identified potentially functional sequences. Comparison of these sequences allowed us to revise the catalog of yeast genes and identify sequence motifs that may be targets of transcriptional regulatory proteins. Some of these conserved sequence motifs reside upstream of genes with similar functional annotations or similar expression patterns or those bound by the same transcription factor and are thus good candidates for functional regulatory sequences.

AphidBase: A centralized bioinformatic resource for annotation of the pea aphid genome

PubMed Central

Legeai, Fabrice; Shigenobu, Shuji; Gauthier, Jean-Pierre; Colbourne, John; Rispe, Claude; Collin, Olivier; Richards, Stephen; Wilson, Alex C. C.; Tagu, Denis

2015-01-01

AphidBase is a centralized bioinformatic resource that was developed to facilitate community annotation of the pea aphid genome by the International Aphid Genomics Consortium (IAGC). The AphidBase Information System designed to organize and distribute genomic data and annotations for a large international community was constructed using open source software tools from the Generic Model Organism Database (GMOD). The system includes Apollo and GBrowse utilities as well as a wiki, blast search capabilities and a full text search engine. AphidBase strongly supported community cooperation and coordination in the curation of gene models during community annotation of the pea aphid genome. AphidBase can be accessed at http://www.aphidbase.com. PMID:20482635

Chado controller: advanced annotation management with a community annotation system.

PubMed

Guignon, Valentin; Droc, Gaëtan; Alaux, Michael; Baurens, Franc-Christophe; Garsmeur, Olivier; Poiron, Claire; Carver, Tim; Rouard, Mathieu; Bocs, Stéphanie

2012-04-01

We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl. The Chado Controller package is available for download at http://www.gnpannot.org/content/chado-controller and runs on any Unix-like operating system, and documentation is available at http://www.gnpannot.org/content/chado-controller-doc The system can be tested using the GNPAnnot Sandbox at http://www.gnpannot.org/content/gnpannot-sandbox-form valentin.guignon@cirad.fr; stephanie.sidibe-bocs@cirad.fr Supplementary data are available at Bioinformatics online.

Transcriptome sequence analysis of an ornamental plant, Ananas comosus var. bracteatus, revealed the potential unigenes involved in terpenoid and phenylpropanoid biosynthesis.

PubMed

Ma, Jun; Kanakala, S; He, Yehua; Zhang, Junli; Zhong, Xiaolan

2015-01-01

Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis. The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus.

Transcriptome Sequence Analysis of an Ornamental Plant, Ananas comosus var. bracteatus, Revealed the Potential Unigenes Involved in Terpenoid and Phenylpropanoid Biosynthesis

PubMed Central

Ma, Jun; Kanakala, S.; He, Yehua; Zhang, Junli; Zhong, Xiaolan

2015-01-01

Background Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. Results The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis. Conclusion The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus. PMID:25769053

Cazymes Analysis Toolkit (CAT): Webservice for searching and analyzing carbohydrateactive enzymes in a newly sequenced organism using CAZy database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karpinets, Tatiana V; Park, Byung; Syed, Mustafa H

2010-01-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire non-redundant sequences of the CAZy database. Themore » second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains (DUF) and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit (CAT), and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.« less

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

CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

PubMed

Park, Byung H; Karpinets, Tatiana V; Syed, Mustafa H; Leuze, Michael R; Uberbacher, Edward C

2010-12-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.

OrthoDB v8: update of the hierarchical catalog of orthologs and the underlying free software.

PubMed

Kriventseva, Evgenia V; Tegenfeldt, Fredrik; Petty, Tom J; Waterhouse, Robert M; Simão, Felipe A; Pozdnyakov, Igor A; Ioannidis, Panagiotis; Zdobnov, Evgeny M

2015-01-01

Orthology, refining the concept of homology, is the cornerstone of evolutionary comparative studies. With the ever-increasing availability of genomic data, inference of orthology has become instrumental for generating hypotheses about gene functions crucial to many studies. This update of the OrthoDB hierarchical catalog of orthologs (http://www.orthodb.org) covers 3027 complete genomes, including the most comprehensive set of 87 arthropods, 61 vertebrates, 227 fungi and 2627 bacteria (sampling the most complete and representative genomes from over 11,000 available). In addition to the most extensive integration of functional annotations from UniProt, InterPro, GO, OMIM, model organism phenotypes and COG functional categories, OrthoDB uniquely provides evolutionary annotations including rates of ortholog sequence divergence, copy-number profiles, sibling groups and gene architectures. We re-designed the entirety of the OrthoDB website from the underlying technology to the user interface, enabling the user to specify species of interest and to select the relevant orthology level by the NCBI taxonomy. The text searches allow use of complex logic with various identifiers of genes, proteins, domains, ontologies or annotation keywords and phrases. Gene copy-number profiles can also be queried. This release comes with the freely available underlying ortholog clustering pipeline (http://www.orthodb.org/software). © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

PubMed Central

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

PubMed

Ramkissoon, Kevin R; Miller, Jennifer K; Ojha, Sunil; Watson, Douglas S; Bomar, Martha G; Galande, Amit K; Shearer, Alexander G

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

A brief introduction to web-based genome browsers.

PubMed

Wang, Jun; Kong, Lei; Gao, Ge; Luo, Jingchu

2013-03-01

Genome browser provides a graphical interface for users to browse, search, retrieve and analyze genomic sequence and annotation data. Web-based genome browsers can be classified into general genome browsers with multiple species and species-specific genome browsers. In this review, we attempt to give an overview for the main functions and features of web-based genome browsers, covering data visualization, retrieval, analysis and customization. To give a brief introduction to the multiple-species genome browser, we describe the user interface and main functions of the Ensembl and UCSC genome browsers using the human alpha-globin gene cluster as an example. We further use the MSU and the Rice-Map genome browsers to show some special features of species-specific genome browser, taking a rice transcription factor gene OsSPL14 as an example.

Inferring transposons activity chronology by TRANScendence - TEs database and de-novo mining tool.

PubMed

Startek, Michał Piotr; Nogły, Jakub; Gromadka, Agnieszka; Grzebelus, Dariusz; Gambin, Anna

2017-10-16

The constant progress in sequencing technology leads to ever increasing amounts of genomic data. In the light of current evidence transposable elements (TEs for short) are becoming useful tools for learning about the evolution of host genome. Therefore the software for genome-wide detection and analysis of TEs is of great interest. Here we describe the computational tool for mining, classifying and storing TEs from newly sequenced genomes. This is an online, web-based, user-friendly service, enabling users to upload their own genomic data, and perform de-novo searches for TEs. The detected TEs are automatically analyzed, compared to reference databases, annotated, clustered into families, and stored in TEs repository. Also, the genome-wide nesting structure of found elements are detected and analyzed by new method for inferring evolutionary history of TEs. We illustrate the functionality of our tool by performing a full-scale analyses of TE landscape in Medicago truncatula genome. TRANScendence is an effective tool for the de-novo annotation and classification of transposable elements in newly-acquired genomes. Its streamlined interface makes it well-suited for evolutionary studies.

Bioinformatics and genomic analysis of transposable elements in eukaryotic genomes.

PubMed

Janicki, Mateusz; Rooke, Rebecca; Yang, Guojun

2011-08-01

A major portion of most eukaryotic genomes are transposable elements (TEs). During evolution, TEs have introduced profound changes to genome size, structure, and function. As integral parts of genomes, the dynamic presence of TEs will continue to be a major force in reshaping genomes. Early computational analyses of TEs in genome sequences focused on filtering out "junk" sequences to facilitate gene annotation. When the high abundance and diversity of TEs in eukaryotic genomes were recognized, these early efforts transformed into the systematic genome-wide categorization and classification of TEs. The availability of genomic sequence data reversed the classical genetic approaches to discovering new TE families and superfamilies. Curated TE databases and their accurate annotation of genome sequences in turn facilitated the studies on TEs in a number of frontiers including: (1) TE-mediated changes of genome size and structure, (2) the influence of TEs on genome and gene functions, (3) TE regulation by host, (4) the evolution of TEs and their population dynamics, and (5) genomic scale studies of TE activity. Bioinformatics and genomic approaches have become an integral part of large-scale studies on TEs to extract information with pure in silico analyses or to assist wet lab experimental studies. The current revolution in genome sequencing technology facilitates further progress in the existing frontiers of research and emergence of new initiatives. The rapid generation of large-sequence datasets at record low costs on a routine basis is challenging the computing industry on storage capacity and manipulation speed and the bioinformatics community for improvement in algorithms and their implementations.

The integrated web service and genome database for agricultural plants with biotechnology information

PubMed Central

Kim, ChangKug; Park, DongSuk; Seol, YoungJoo; Hahn, JangHo

2011-01-01

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a Web based relational database for agricultural plants with biotechnology information. The NABIC has concentrated on functional genomics of major agricultural plants, building an integrated biotechnology database for agro-biotech information that focuses on genomics of major agricultural resources. This genome database provides annotated genome information from 1,039,823 records mapped to rice, Arabidopsis, and Chinese cabbage. PMID:21887015

SEED Servers: High-Performance Access to the SEED Genomes, Annotations, and Metabolic Models

PubMed Central

Aziz, Ramy K.; Devoid, Scott; Disz, Terrence; Edwards, Robert A.; Henry, Christopher S.; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Stevens, Rick L.; Vonstein, Veronika; Xia, Fangfang

2012-01-01

The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users. PMID:23110173

ePIANNO: ePIgenomics ANNOtation tool.

PubMed

Liu, Chia-Hsin; Ho, Bing-Ching; Chen, Chun-Ling; Chang, Ya-Hsuan; Hsu, Yi-Chiung; Li, Yu-Cheng; Yuan, Shin-Sheng; Huang, Yi-Huan; Chang, Chi-Sheng; Li, Ker-Chau; Chen, Hsuan-Yu

2016-01-01

Recently, with the development of next generation sequencing (NGS), the combination of chromatin immunoprecipitation (ChIP) and NGS, namely ChIP-seq, has become a powerful technique to capture potential genomic binding sites of regulatory factors, histone modifications and chromatin accessible regions. For most researchers, additional information including genomic variations on the TF binding site, allele frequency of variation between different populations, variation associated disease, and other neighbour TF binding sites are essential to generate a proper hypothesis or a meaningful conclusion. Many ChIP-seq datasets had been deposited on the public domain to help researchers make new discoveries. However, researches are often intimidated by the complexity of data structure and largeness of data volume. Such information would be more useful if they could be combined or downloaded with ChIP-seq data. To meet such demands, we built a webtool: ePIgenomic ANNOtation tool (ePIANNO, http://epianno.stat.sinica.edu.tw/index.html). ePIANNO is a web server that combines SNP information of populations (1000 Genomes Project) and gene-disease association information of GWAS (NHGRI) with ChIP-seq (hmChIP, ENCODE, and ROADMAP epigenomics) data. ePIANNO has a user-friendly website interface allowing researchers to explore, navigate, and extract data quickly. We use two examples to demonstrate how users could use functions of ePIANNO webserver to explore useful information about TF related genomic variants. Users could use our query functions to search target regions, transcription factors, or annotations. ePIANNO may help users to generate hypothesis or explore potential biological functions for their studies.

Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project.

PubMed

Aggarwal, Gautam; Worthey, E A; McDonagh, Paul D; Myler, Peter J

2003-06-07

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces. Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODONUSAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence. An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2003-01-01

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

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).

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Complete genome sequence of an attenuated Sparfloxacin-resistant Streptococcus agalactiae strain 138spar

USDA-ARS?s Scientific Manuscript database

The complete genome of a sparfloxacin-resistant Streptococcus agalactiae vaccine strain 138spar is 1,838,126 bp in size. The genome has 1892 coding sequences and 82 RNAs. The annotation of the genome is added by the NCBI Prokaryotic Genome Annotation Pipeline. The publishing of this genome will allo...

CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.

PubMed

Testa, Alison C; Hane, James K; Ellwood, Simon R; Oliver, Richard P

2015-03-11

The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available ( https://sourceforge.net/projects/codingquarry/ ), and suitable for incorporation into genome annotation pipelines.

Analysis of disease-associated objects at the Rat Genome Database

PubMed Central

Wang, Shur-Jen; Laulederkind, Stanley J. F.; Hayman, G. T.; Smith, Jennifer R.; Petri, Victoria; Lowry, Timothy F.; Nigam, Rajni; Dwinell, Melinda R.; Worthey, Elizabeth A.; Munzenmaier, Diane H.; Shimoyama, Mary; Jacob, Howard J.

2013-01-01

The Rat Genome Database (RGD) is the premier resource for genetic, genomic and phenotype data for the laboratory rat, Rattus norvegicus. In addition to organizing biological data from rats, the RGD team focuses on manual curation of gene–disease associations for rat, human and mouse. In this work, we have analyzed disease-associated strains, quantitative trait loci (QTL) and genes from rats. These disease objects form the basis for seven disease portals. Among disease portals, the cardiovascular disease and obesity/metabolic syndrome portals have the highest number of rat strains and QTL. These two portals share 398 rat QTL, and these shared QTL are highly concentrated on rat chromosomes 1 and 2. For disease-associated genes, we performed gene ontology (GO) enrichment analysis across portals using RatMine enrichment widgets. Fifteen GO terms, five from each GO aspect, were selected to profile enrichment patterns of each portal. Of the selected biological process (BP) terms, ‘regulation of programmed cell death’ was the top enriched term across all disease portals except in the obesity/metabolic syndrome portal where ‘lipid metabolic process’ was the most enriched term. ‘Cytosol’ and ‘nucleus’ were common cellular component (CC) annotations for disease genes, but only the cancer portal genes were highly enriched with ‘nucleus’ annotations. Similar enrichment patterns were observed in a parallel analysis using the DAVID functional annotation tool. The relationship between the preselected 15 GO terms and disease terms was examined reciprocally by retrieving rat genes annotated with these preselected terms. The individual GO term–annotated gene list showed enrichment in physiologically related diseases. For example, the ‘regulation of blood pressure’ genes were enriched with cardiovascular disease annotations, and the ‘lipid metabolic process’ genes with obesity annotations. Furthermore, we were able to enhance enrichment of neurological diseases by combining ‘G-protein coupled receptor binding’ annotated genes with ‘protein kinase binding’ annotated genes. Database URL: http://rgd.mcw.edu PMID:23794737

MIPS: analysis and annotation of proteins from whole genomes in 2005

PubMed Central

Mewes, H. W.; Frishman, D.; Mayer, K. F. X.; Münsterkötter, M.; Noubibou, O.; Pagel, P.; Rattei, T.; Oesterheld, M.; Ruepp, A.; Stümpflen, V.

2006-01-01

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein–protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (). PMID:16381839

MIPS: analysis and annotation of proteins from whole genomes in 2005.

PubMed

Mewes, H W; Frishman, D; Mayer, K F X; Münsterkötter, M; Noubibou, O; Pagel, P; Rattei, T; Oesterheld, M; Ruepp, A; Stümpflen, V

2006-01-01

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

India Allele Finder: a web-based annotation tool for identifying common alleles in next-generation sequencing data of Indian origin.

PubMed

Zhang, Jimmy F; James, Francis; Shukla, Anju; Girisha, Katta M; Paciorkowski, Alex R

2017-06-27

We built India Allele Finder, an online searchable database and command line tool, that gives researchers access to variant frequencies of Indian Telugu individuals, using publicly available fastq data from the 1000 Genomes Project. Access to appropriate population-based genomic variant annotation can accelerate the interpretation of genomic sequencing data. In particular, exome analysis of individuals of Indian descent will identify population variants not reflected in European exomes, complicating genomic analysis for such individuals. India Allele Finder offers improved ease-of-use to investigators seeking to identify and annotate sequencing data from Indian populations. We describe the use of India Allele Finder to identify common population variants in a disease quartet whole exome dataset, reducing the number of candidate single nucleotide variants from 84 to 7. India Allele Finder is freely available to investigators to annotate genomic sequencing data from Indian populations. Use of India Allele Finder allows efficient identification of population variants in genomic sequencing data, and is an example of a population-specific annotation tool that simplifies analysis and encourages international collaboration in genomics research.

Whole genome annotation and comparative genomic analyses of bio-control fungus Purpureocillium lilacinum.

PubMed

Prasad, Pushplata; Varshney, Deepti; Adholeya, Alok

2015-11-25

The fungus Purpureocillium lilacinum is widely known as a biological control agent against plant parasitic nematodes. This research article consists of genomic annotation of the first draft of whole genome sequence of P. lilacinum. The study aims to decipher the putative genetic components of the fungus involved in nematode pathogenesis by performing comparative genomic analysis with nine closely related fungal species in Hypocreales. de novo genomic assembly was done and a total of 301 scaffolds were constructed for P. lilacinum genomic DNA. By employing structural genome prediction models, 13, 266 genes coding for proteins were predicted in the genome. Approximately 73% of the predicted genes were functionally annotated using Blastp, InterProScan and Gene Ontology. A 14.7% fraction of the predicted genes shared significant homology with genes in the Pathogen Host Interactions (PHI) database. The phylogenomic analysis carried out using maximum likelihood RAxML algorithm provided insight into the evolutionary relationship of P. lilacinum. In congruence with other closely related species in the Hypocreales namely, Metarhizium spp., Pochonia chlamydosporia, Cordyceps militaris, Trichoderma reesei and Fusarium spp., P. lilacinum has large gene sets coding for G-protein coupled receptors (GPCRs), proteases, glycoside hydrolases and carbohydrate esterases that are required for degradation of nematode-egg shell components. Screening of the genome by Antibiotics & Secondary Metabolite Analysis Shell (AntiSMASH) pipeline indicated that the genome potentially codes for a variety of secondary metabolites, possibly required for adaptation to heterogeneous lifestyles reported for P. lilacinum. Significant up-regulation of subtilisin-like serine protease genes in presence of nematode eggs in quantitative real-time analyses suggested potential role of serine proteases in nematode pathogenesis. The data offer a better understanding of Purpureocillium lilacinum genome and will enhance our understanding on the molecular mechanism involved in nematophagy.

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies.

PubMed

Zeng, Lu; Kortschak, R Daniel; Raison, Joy M; Bertozzi, Terry; Adelson, David L

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package.

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies

PubMed Central

Zeng, Lu; Kortschak, R. Daniel; Raison, Joy M.

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package. PMID:29538441

GrTEdb: the first web-based database of transposable elements in cotton (Gossypium raimondii).

PubMed

Xu, Zhenzhen; Liu, Jing; Ni, Wanchao; Peng, Zhen; Guo, Yue; Ye, Wuwei; Huang, Fang; Zhang, Xianggui; Xu, Peng; Guo, Qi; Shen, Xinlian; Du, Jianchang

2017-01-01

Although several diploid and tetroploid Gossypium species genomes have been sequenced, the well annotated web-based transposable elements (TEs) database is lacking. To better understand the roles of TEs in structural, functional and evolutionary dynamics of the cotton genome, a comprehensive, specific, and user-friendly web-based database, Gossypium raimondii transposable elements database (GrTEdb), was constructed. A total of 14 332 TEs were structurally annotated and clearly categorized in G. raimondii genome, and these elements have been classified into seven distinct superfamilies based on the order of protein-coding domains, structures and/or sequence similarity, including 2929 Copia-like elements, 10 368 Gypsy-like elements, 299 L1 , 12 Mutators , 435 PIF-Harbingers , 275 CACTAs and 14 Helitrons . Meanwhile, the web-based sequence browsing, searching, downloading and blast tool were implemented to help users easily and effectively to annotate the TEs or TE fragments in genomic sequences from G. raimondii and other closely related Gossypium species. GrTEdb provides resources and information related with TEs in G. raimondii , and will facilitate gene and genome analyses within or across Gossypium species, evaluating the impact of TEs on their host genomes, and investigating the potential interaction between TEs and protein-coding genes in Gossypium species. http://www.grtedb.org/. © The Author(s) 2017. Published by Oxford University Press.

Exploring Protein Function Using the Saccharomyces Genome Database.

PubMed

Wong, Edith D

2017-01-01

Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

ITEP: an integrated toolkit for exploration of microbial pan-genomes.

PubMed

Benedict, Matthew N; Henriksen, James R; Metcalf, William W; Whitaker, Rachel J; Price, Nathan D

2014-01-03

Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP's capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.

The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization.

PubMed

Nelson, David R; Khraiwesh, Basel; Fu, Weiqi; Alseekh, Saleh; Jaiswal, Ashish; Chaiboonchoe, Amphun; Hazzouri, Khaled M; O'Connor, Matthew J; Butterfoss, Glenn L; Drou, Nizar; Rowe, Jillian D; Harb, Jamil; Fernie, Alisdair R; Gunsalus, Kristin C; Salehi-Ashtiani, Kourosh

2017-06-17

To investigate the phenomic and genomic traits that allow green algae to survive in deserts, we characterized a ubiquitous species, Chloroidium sp. UTEX 3007 , which we isolated from multiple locations in the United Arab Emirates (UAE). Metabolomic analyses of Chloroidium sp. UTEX 3007 indicated that the alga accumulates a broad range of carbon sources, including several desiccation tolerance-promoting sugars and unusually large stores of palmitate. Growth assays revealed capacities to grow in salinities from zero to 60 g/L and to grow heterotrophically on >40 distinct carbon sources. Assembly and annotation of genomic reads yielded a 52.5 Mbp genome with 8153 functionally annotated genes. Comparison with other sequenced green algae revealed unique protein families involved in osmotic stress tolerance and saccharide metabolism that support phenomic studies. Our results reveal the robust and flexible biology utilized by a green alga to successfully inhabit a desert coastline.

Genomic and functional characterisation of two Enterococcus strains isolated from Cotija cheese and their potential role in ripening.

PubMed

Olvera-García, Myrna; Sanchez-Flores, Alejandro; Quirasco Baruch, Maricarmen

2018-03-01

Enterococcus spp. are present in the native microbiota of many traditional fermented foods. Their ability to produce antibacterial compounds, mainly against Listeria monocytogenes, has raised interest recently. However, there is scarce information about their proteolytic and lipolytic potential, and their biotechnological application is currently limited because enterococcal strains have been related to nosocomial infections. In this work, next-generation sequencing and optimised bioinformatic pipelines were used to annotate the genomes of two Enterococcus strains-one E. faecium and one E. faecalis-isolated from the Mexican artisanal ripened Cotija cheese. A battery of genes involved in their proteolytic system was annotated. Genes coding for lipases, esterases and other enzymes whose final products contribute to cheese aroma and flavour were identified as well. As for the production of antibacterial compounds, several peptidoglycan hydrolase- and bacteriocin-coding genes were identified in both genomes experimentally and by bioinformatic analyses. E. faecalis showed resistance to aminoglycosides and E. faecium to aminoglycosides and macrolides, as predicted by the genome functional annotation. No pathogenicity islands were found in any of the strains, although traits such as the ability of biofilm formation and cell aggregation were observed. Finally, a comparative genomic analysis was able to discriminate between the food strains isolated and nosocomial strains. In summary, pathogenic strains are resistant to a wide range of antibiotics and contain virulence factors that cause host damage; in contrast, food strains display less antibiotic resistance, include genes that encode class II bacteriocins and express virulence factors associated with host colonisation rather than invasion.

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. Copyright © 2016 by the Genetics Society of America.

Mycobacteriophage genome database.

PubMed

Joseph, Jerrine; Rajendran, Vasanthi; Hassan, Sameer; Kumar, Vanaja

2011-01-01

Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php.

PanCoreGen - Profiling, detecting, annotating protein-coding genes in microbial genomes.

PubMed

Paul, Sandip; Bhardwaj, Archana; Bag, Sumit K; Sokurenko, Evgeni V; Chattopadhyay, Sujay

2015-12-01

A large amount of genomic data, especially from multiple isolates of a single species, has opened new vistas for microbial genomics analysis. Analyzing the pan-genome (i.e. the sum of genetic repertoire) of microbial species is crucial in understanding the dynamics of molecular evolution, where virulence evolution is of major interest. Here we present PanCoreGen - a standalone application for pan- and core-genomic profiling of microbial protein-coding genes. PanCoreGen overcomes key limitations of the existing pan-genomic analysis tools, and develops an integrated annotation-structure for a species-specific pan-genomic profile. It provides important new features for annotating draft genomes/contigs and detecting unidentified genes in annotated genomes. It also generates user-defined group-specific datasets within the pan-genome. Interestingly, analyzing an example-set of Salmonella genomes, we detect potential footprints of adaptive convergence of horizontally transferred genes in two human-restricted pathogenic serovars - Typhi and Paratyphi A. Overall, PanCoreGen represents a state-of-the-art tool for microbial phylogenomics and pathogenomics study. Copyright © 2015 Elsevier Inc. All rights reserved.

The Biological Reference Repository (BioR): a rapid and flexible system for genomics annotation.

PubMed

Kocher, Jean-Pierre A; Quest, Daniel J; Duffy, Patrick; Meiners, Michael A; Moore, Raymond M; Rider, David; Hossain, Asif; Hart, Steven N; Dinu, Valentin

2014-07-01

The Biological Reference Repository (BioR) is a toolkit for annotating variants. BioR stores public and user-specific annotation sources in indexed JSON-encoded flat files (catalogs). The BioR toolkit provides the functionality to combine and retrieve annotation from these catalogs via the command-line interface. Several catalogs from commonly used annotation sources and instructions for creating user-specific catalogs are provided. Commands from the toolkit can be combined with other UNIX commands for advanced annotation processing. We also provide instructions for the development of custom annotation pipelines. The package is implemented in Java and makes use of external tools written in Java and Perl. The toolkit can be executed on Mac OS X 10.5 and above or any Linux distribution. The BioR application, quickstart, and user guide documents and many biological examples are available at http://bioinformaticstools.mayo.edu. © The Author 2014. Published by Oxford University Press.

A computational genomics pipeline for prokaryotic sequencing projects

PubMed Central

Kislyuk, Andrey O.; Katz, Lee S.; Agrawal, Sonia; Hagen, Matthew S.; Conley, Andrew B.; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C.; Sammons, Scott A.; Govil, Dhwani; Mair, Raydel D.; Tatti, Kathleen M.; Tondella, Maria L.; Harcourt, Brian H.; Mayer, Leonard W.; Jordan, I. King

2010-01-01

Motivation: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. Results: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. Availability and implementation: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems. Contact: king.jordan@biology.gatech.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20519285

MIPS: a database for genomes and protein sequences.

PubMed Central

Mewes, H W; Heumann, K; Kaps, A; Mayer, K; Pfeiffer, F; Stocker, S; Frishman, D

1999-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Martinsried near Munich, Germany, develops and maintains genome oriented databases. It is commonplace that the amount of sequence data available increases rapidly, but not the capacity of qualified manual annotation at the sequence databases. Therefore, our strategy aims to cope with the data stream by the comprehensive application of analysis tools to sequences of complete genomes, the systematic classification of protein sequences and the active support of sequence analysis and functional genomics projects. This report describes the systematic and up-to-date analysis of genomes (PEDANT), a comprehensive database of the yeast genome (MYGD), a database reflecting the progress in sequencing the Arabidopsis thaliana genome (MATD), the database of assembled, annotated human EST clusters (MEST), and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). MIPS provides access through its WWW server (http://www.mips.biochem.mpg.de) to a spectrum of generic databases, including the above mentioned as well as a database of protein families (PROTFAM), the MITOP database, and the all-against-all FASTA database. PMID:9847138

Lessons learned from the initial sequencing of the pig genome: comparative analysis of an 8 Mb region of pig chromosome 17

PubMed Central

Hart, Elizabeth A; Caccamo, Mario; Harrow, Jennifer L; Humphray, Sean J; Gilbert, James GR; Trevanion, Steve; Hubbard, Tim; Rogers, Jane; Rothschild, Max F

2007-01-01

Background We describe here the sequencing, annotation and comparative analysis of an 8 Mb region of pig chromosome 17, which provides a useful test region to assess coverage and quality for the pig genome sequencing project. We report our findings comparing the annotation of draft sequence assembled at different depths of coverage. Results Within this region we annotated 71 loci, of which 53 are orthologous to human known coding genes. When compared to the syntenic regions in human (20q13.13-q13.33) and mouse (chromosome 2, 167.5 Mb-178.3 Mb), this region was found to be highly conserved with respect to gene order. The most notable difference between the three species is the presence of a large expansion of zinc finger coding genes and pseudogenes on mouse chromosome 2 between Edn3 and Phactr3 that is absent from pig and human. All of our annotation has been made publicly available in the Vertebrate Genome Annotation browser, VEGA. We assessed the impact of coverage on sequence assembly across this region and found, as expected, that increased sequence depth resulted in fewer, longer contigs. One-third of our annotated loci could not be fully re-aligned back to the low coverage version of the sequence, principally because the transcripts are fragmented over several contigs. Conclusion We have demonstrated the considerable advantages of sequencing at increased read depths and discuss the implications that lower coverage sequence may have on subsequent comparative and functional studies, particularly those involving complex loci such as GNAS. PMID:17705864

Ginseng Genome Database: an open-access platform for genomics of Panax ginseng.

PubMed

Jayakodi, Murukarthick; Choi, Beom-Soon; Lee, Sang-Choon; Kim, Nam-Hoon; Park, Jee Young; Jang, Woojong; Lakshmanan, Meiyappan; Mohan, Shobhana V G; Lee, Dong-Yup; Yang, Tae-Jin

2018-04-12

The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years. Ginsenosides, which have significant pharmacological effects on human health, are the foremost bioactive constituents in this plant. Having realized the importance of this plant to humans, an integrated omics resource becomes indispensable to facilitate genomic research, molecular breeding and pharmacological study of this herb. The first draft genome sequences of P. ginseng cultivar "Chunpoong" were reported recently. Here, using the draft genome, transcriptome, and functional annotation datasets of P. ginseng, we have constructed the Ginseng Genome Database http://ginsengdb.snu.ac.kr /, the first open-access platform to provide comprehensive genomic resources of P. ginseng. The current version of this database provides the most up-to-date draft genome sequence (of approximately 3000 Mbp of scaffold sequences) along with the structural and functional annotations for 59,352 genes and digital expression of genes based on transcriptome data from different tissues, growth stages and treatments. In addition, tools for visualization and the genomic data from various analyses are provided. All data in the database were manually curated and integrated within a user-friendly query page. This database provides valuable resources for a range of research fields related to P. ginseng and other species belonging to the Apiales order as well as for plant research communities in general. Ginseng genome database can be accessed at http://ginsengdb.snu.ac.kr /.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives.

PubMed

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives

PubMed Central

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information. PMID:28234924

Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics

PubMed Central

Tzika, Athanasia C.; Ullate-Agote, Asier; Grbic, Djordje; Milinkovitch, Michel C.

2015-01-01

Despite the availability of deep-sequencing techniques, genomic and transcriptomic data remain unevenly distributed across phylogenetic groups. For example, reptiles are poorly represented in sequence databases, hindering functional evolutionary and developmental studies in these lineages substantially more diverse than mammals. In addition, different studies use different assembly and annotation protocols, inhibiting meaningful comparisons. Here, we present the “Reptilian Transcriptomes Database 2.0,” which provides extensive annotation of transcriptomes and genomes from species covering the major reptilian lineages. To this end, we sequenced normalized complementary DNA libraries of multiple adult tissues and various embryonic stages of the leopard gecko and the corn snake and gathered published reptilian sequence data sets from representatives of the four extant orders of reptiles: Squamata (snakes and lizards), the tuatara, crocodiles, and turtles. The LANE runner 2.0 software was implemented to annotate all assemblies within a single integrated pipeline. We show that this approach increases the annotation completeness of the assembled transcriptomes/genomes. We then built large concatenated protein alignments of single-copy genes and inferred phylogenetic trees that support the positions of turtles and the tuatara as sister groups of Archosauria and Squamata, respectively. The Reptilian Transcriptomes Database 2.0 resource will be updated to include selected new data sets as they become available, thus making it a reference for differential expression studies, comparative genomics and transcriptomics, linkage mapping, molecular ecology, and phylogenomic analyses involving reptiles. The database is available at www.reptilian-transcriptomes.org and can be enquired using a wwwblast server installed at the University of Geneva. PMID:26133641

Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

PubMed

Patel, Sejal; Roncaglia, Paola; Lovering, Ruth C

2015-06-06

People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is known to be associated with a combination of genetic and environmental factors. Neurexins and neuroligins play a key role in synaptogenesis and neurexin-neuroligin adhesion is one of several processes that have been implicated in autism spectrum disorders. In this report we describe the manual annotation of a selection of gene products known to be associated with autism and/or the neurexin-neuroligin-SHANK complex and demonstrate how a focused annotation approach leads to the creation of more descriptive Gene Ontology (GO) terms, as well as an increase in both the number of gene product annotations and their granularity, thus improving the data available in the GO database. The manual annotations we describe will impact on the functional analysis of a variety of future autism-relevant datasets. Comprehensive gene annotation is an essential aspect of genomic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis tools affects the effective interpretation of data obtained through genome wide association studies, next generation sequencing, proteomic and transcriptomic datasets.

AncestrySNPminer: A bioinformatics tool to retrieve and develop ancestry informative SNP panels

PubMed Central

Amirisetty, Sushil; Khurana Hershey, Gurjit K.; Baye, Tesfaye M.

2012-01-01

A wealth of genomic information is available in public and private databases. However, this information is underutilized for uncovering population specific and functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a faster and cost effective approach for investigating the number of SNPs that are informative for ancestry. In this study, we present AncestrySNPminer, the first web-based bioinformatics tool specifically designed to retrieve Ancestry Informative Markers (AIMs) from genomic data sets and link these informative markers to genes and ontological annotation classes. The tool includes an automated and simple “scripting at the click of a button” functionality that enables researchers to perform various population genomics statistical analyses methods with user friendly querying and filtering of data sets across various populations through a single web interface. AncestrySNPminer can be freely accessed at https://research.cchmc.org/mershalab/AncestrySNPminer/login.php. PMID:22584067

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-09-04

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-06-01

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

Transcriptome analysis reveals the time of the fourth round of genome duplication in common carp (Cyprinus carpio)

PubMed Central

2012-01-01

Background Common carp (Cyprinus carpio) is thought to have undergone one extra round of genome duplication compared to zebrafish. Transcriptome analysis has been used to study the existence and timing of genome duplication in species for which genome sequences are incomplete. Large-scale transcriptome data for the common carp genome should help reveal the timing of the additional duplication event. Results We have sequenced the transcriptome of common carp using 454 pyrosequencing. After assembling the 454 contigs and the published common carp sequences together, we obtained 49,669 contigs and identified genes using homology searches and an ab initio method. We identified 4,651 orthologous pairs between common carp and zebrafish and found 129,984 paralogous pairs within the common carp. An estimation of the synonymous substitution rate in the orthologous pairs indicated that common carp and zebrafish diverged 120 million years ago (MYA). We identified one round of genome duplication in common carp and estimated that it had occurred 5.6 to 11.3 MYA. In zebrafish, no genome duplication event after speciation was observed, suggesting that, compared to zebrafish, common carp had undergone an additional genome duplication event. We annotated the common carp contigs with Gene Ontology terms and KEGG pathways. Compared with zebrafish gene annotations, we found that a set of biological processes and pathways were enriched in common carp. Conclusions The assembled contigs helped us to estimate the time of the fourth-round of genome duplication in common carp. The resource that we have built as part of this study will help advance functional genomics and genome annotation studies in the future. PMID:22424280

Chado Controller: advanced annotation management with a community annotation system

PubMed Central

Guignon, Valentin; Droc, Gaëtan; Alaux, Michael; Baurens, Franc-Christophe; Garsmeur, Olivier; Poiron, Claire; Carver, Tim; Rouard, Mathieu; Bocs, Stéphanie

2012-01-01

Summary: We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl. Availability: The Chado Controller package is available for download at http://www.gnpannot.org/content/chado-controller and runs on any Unix-like operating system, and documentation is available at http://www.gnpannot.org/content/chado-controller-doc The system can be tested using the GNPAnnot Sandbox at http://www.gnpannot.org/content/gnpannot-sandbox-form Contact: valentin.guignon@cirad.fr; stephanie.sidibe-bocs@cirad.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22285827

MEETING: Chlamydomonas Annotation Jamboree - October 2003

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grossman, Arthur R

2007-04-13

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

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes.

PubMed

Lowe, Todd M; Chan, Patricia P

2016-07-08

High-throughput genome sequencing continues to grow the need for rapid, accurate genome annotation and tRNA genes constitute the largest family of essential, ever-present non-coding RNA genes. Newly developed tRNAscan-SE 2.0 has advanced the state-of-the-art methodology in tRNA gene detection and functional prediction, captured by rich new content of the companion Genomic tRNA Database. Previously, web-server tRNA detection was isolated from knowledge of existing tRNAs and their annotation. In this update of the tRNAscan-SE On-line resource, we tie together improvements in tRNA classification with greatly enhanced biological context via dynamically generated links between web server search results, the most relevant genes in the GtRNAdb and interactive, rich genome context provided by UCSC genome browsers. The tRNAscan-SE On-line web server can be accessed at http://trna.ucsc.edu/tRNAscan-SE/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Protein Function Prediction: Problems and Pitfalls.

PubMed

Pearson, William R

2015-09-03

The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity," and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one-size-fits-all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood. Copyright © 2015 John Wiley & Sons, Inc.

PlantRNA, a database for tRNAs of photosynthetic eukaryotes.

PubMed

Cognat, Valérie; Pawlak, Gaël; Duchêne, Anne-Marie; Daujat, Magali; Gigant, Anaïs; Salinas, Thalia; Michaud, Morgane; Gutmann, Bernard; Giegé, Philippe; Gobert, Anthony; Maréchal-Drouard, Laurence

2013-01-01

PlantRNA database (http://plantrna.ibmp.cnrs.fr/) compiles transfer RNA (tRNA) gene sequences retrieved from fully annotated plant nuclear, plastidial and mitochondrial genomes. The set of annotated tRNA gene sequences has been manually curated for maximum quality and confidence. The novelty of this database resides in the inclusion of biological information relevant to the function of all the tRNAs entered in the library. This includes 5'- and 3'-flanking sequences, A and B box sequences, region of transcription initiation and poly(T) transcription termination stretches, tRNA intron sequences, aminoacyl-tRNA synthetases and enzymes responsible for tRNA maturation and modification. Finally, data on mitochondrial import of nuclear-encoded tRNAs as well as the bibliome for the respective tRNAs and tRNA-binding proteins are also included. The current annotation concerns complete genomes from 11 organisms: five flowering plants (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Medicago truncatula and Brachypodium distachyon), a moss (Physcomitrella patens), two green algae (Chlamydomonas reinhardtii and Ostreococcus tauri), one glaucophyte (Cyanophora paradoxa), one brown alga (Ectocarpus siliculosus) and a pennate diatom (Phaeodactylum tricornutum). The database will be regularly updated and implemented with new plant genome annotations so as to provide extensive information on tRNA biology to the research community.

Characterization and genome functional analysis of a novel metamitron-degrading strain Rhodococcus sp. MET via both triazinone and phenyl rings cleavage

NASA Astrophysics Data System (ADS)

Fang, Hua; Xu, Tianheng; Cao, Duantao; Cheng, Longyin; Yu, Yunlong

2016-08-01

A novel bacterium capable of utilizing metamitron as the sole source of carbon and energy was isolated from contaminated soil and identified as Rhodococcus sp. MET based on its morphological characteristics, BIOLOG GP2 microplate profile, and 16S rDNA phylogeny. Genome sequencing and functional annotation of the isolate MET showed a 6,340,880 bp genome with a 62.47% GC content and 5,987 protein-coding genes. In total, 5,907 genes were annotated with the COG, GO, KEGG, Pfam, Swiss-Prot, TrEMBL, and nr databases. The degradation rate of metamitron by the isolate MET obviously increased with increasing substrate concentrations from 1 to 10 mg/l and subsequently decreased at 100 mg/l. The optimal pH and temperature for metamitron biodegradation were 7.0 and 20-30 °C, respectively. Based on genome annotation of the metamitron degradation genes and the metabolites detected by HPLC-MS/MS, the following metamitron biodegradation pathways were proposed: 1) Metamitron was transformed into 2-(3-hydrazinyl-2-ethyl)-hydrazono-2-phenylacetic acid by triazinone ring cleavage and further mineralization; 2) Metamitron was converted into 3-methyl-4-amino-6(2-hydroxy-muconic acid)-1,2,4-triazine-5(4H)-one by phenyl ring cleavage and further mineralization. The coexistence of diverse mineralization pathways indicates that our isolate may effectively bioremediate triazinone herbicide-contaminated soils.

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

PubMed

Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

2013-09-02

In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome-wide collection of reference RNA motif regulons is available in the RegPrecise database (http://regprecise.lbl.gov/).

Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations | Office of Cancer Genomics

Cancer.gov

Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are composed of causal "driver" mutations that promote tumor progression along with many more pathologically neutral "passenger" events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers.

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.

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

Illuminating structural proteins in viral "dark matter" with metaproteomics

DOE PAGES

Brum, Jennifer R.; Ignacio-Espinoza, J. Cesar; Kim, Eun -Hae; ...

2016-02-16

Viruses are ecologically important, yet environmental virology is limited by dominance of unannotated genomic sequences representing taxonomic and functional "viral dark matter." Although recent analytical advances are rapidly improving taxonomic annotations, identifying functional darkmatter remains problematic. Here, we apply paired metaproteomics and dsDNA-targeted metagenomics to identify 1,875 virion-associated proteins from the ocean. Over one-half of these proteins were newly functionally annotated and represent abundant and widespread viral metagenome-derived protein clusters (PCs). One primarily unannotated PC dominated the dataset, but structural modeling and genomic context identified this PC as a previously unidentified capsid protein from multiple uncultivated tailed virus families. Furthermore,more » four of the five most abundant PCs in the metaproteome represent capsid proteins containing the HK97-like protein fold previously found in many viruses that infect all three domains of life. The dominance of these proteins within our dataset, as well as their global distribution throughout the world's oceans and seas, supports prior hypotheses that this HK97-like protein fold is the most abundant biological structure on Earth. Altogether, these culture-independent analyses improve virion-associated protein annotations, facilitate the investigation of proteins within natural viral communities, and offer a high-throughput means of illuminating functional viral dark matter.« less

Illuminating structural proteins in viral "dark matter" with metaproteomics.

PubMed

Brum, Jennifer R; Ignacio-Espinoza, J Cesar; Kim, Eun-Hae; Trubl, Gareth; Jones, Robert M; Roux, Simon; VerBerkmoes, Nathan C; Rich, Virginia I; Sullivan, Matthew B

2016-03-01

Viruses are ecologically important, yet environmental virology is limited by dominance of unannotated genomic sequences representing taxonomic and functional "viral dark matter." Although recent analytical advances are rapidly improving taxonomic annotations, identifying functional dark matter remains problematic. Here, we apply paired metaproteomics and dsDNA-targeted metagenomics to identify 1,875 virion-associated proteins from the ocean. Over one-half of these proteins were newly functionally annotated and represent abundant and widespread viral metagenome-derived protein clusters (PCs). One primarily unannotated PC dominated the dataset, but structural modeling and genomic context identified this PC as a previously unidentified capsid protein from multiple uncultivated tailed virus families. Furthermore, four of the five most abundant PCs in the metaproteome represent capsid proteins containing the HK97-like protein fold previously found in many viruses that infect all three domains of life. The dominance of these proteins within our dataset, as well as their global distribution throughout the world's oceans and seas, supports prior hypotheses that this HK97-like protein fold is the most abundant biological structure on Earth. Together, these culture-independent analyses improve virion-associated protein annotations, facilitate the investigation of proteins within natural viral communities, and offer a high-throughput means of illuminating functional viral dark matter.

Illuminating structural proteins in viral “dark matter” with metaproteomics

PubMed Central

Brum, Jennifer R.; Ignacio-Espinoza, J. Cesar; Kim, Eun-Hae; Trubl, Gareth; Jones, Robert M.; Roux, Simon; VerBerkmoes, Nathan C.; Rich, Virginia I.; Sullivan, Matthew B.

2016-01-01

Viruses are ecologically important, yet environmental virology is limited by dominance of unannotated genomic sequences representing taxonomic and functional “viral dark matter.” Although recent analytical advances are rapidly improving taxonomic annotations, identifying functional dark matter remains problematic. Here, we apply paired metaproteomics and dsDNA-targeted metagenomics to identify 1,875 virion-associated proteins from the ocean. Over one-half of these proteins were newly functionally annotated and represent abundant and widespread viral metagenome-derived protein clusters (PCs). One primarily unannotated PC dominated the dataset, but structural modeling and genomic context identified this PC as a previously unidentified capsid protein from multiple uncultivated tailed virus families. Furthermore, four of the five most abundant PCs in the metaproteome represent capsid proteins containing the HK97-like protein fold previously found in many viruses that infect all three domains of life. The dominance of these proteins within our dataset, as well as their global distribution throughout the world’s oceans and seas, supports prior hypotheses that this HK97-like protein fold is the most abundant biological structure on Earth. Together, these culture-independent analyses improve virion-associated protein annotations, facilitate the investigation of proteins within natural viral communities, and offer a high-throughput means of illuminating functional viral dark matter. PMID:26884177

PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes

PubMed Central

Bhawna; Bonthala, V.S.; Gajula, MNV Prasad

2016-01-01

The common bean [Phaseolus vulgaris (L.)] is one of the essential proteinaceous vegetables grown in developing countries. However, its production is challenged by low yields caused by numerous biotic and abiotic stress conditions. Regulatory transcription factors (TFs) symbolize a key component of the genome and are the most significant targets for producing stress tolerant crop and hence functional genomic studies of these TFs are important. Therefore, here we have constructed a web-accessible TFs database for P. vulgaris, called PvTFDB, which contains 2370 putative TF gene models in 49 TF families. This database provides a comprehensive information for each of the identified TF that includes sequence data, functional annotation, SSRs with their primer sets, protein physical properties, chromosomal location, phylogeny, tissue-specific gene expression data, orthologues, cis-regulatory elements and gene ontology (GO) assignment. Altogether, this information would be used in expediting the functional genomic studies of a specific TF(s) of interest. The objectives of this database are to understand functional genomics study of common bean TFs and recognize the regulatory mechanisms underlying various stress responses to ease breeding strategy for variety production through a couple of search interfaces including gene ID, functional annotation and browsing interfaces including by family and by chromosome. This database will also serve as a promising central repository for researchers as well as breeders who are working towards crop improvement of legume crops. In addition, this database provide the user unrestricted public access and the user can download entire data present in the database freely. Database URL: http://www.multiomics.in/PvTFDB/ PMID:27465131

STINGRAY: system for integrated genomic resources and analysis.

PubMed

Wagner, Glauber; Jardim, Rodrigo; Tschoeke, Diogo A; Loureiro, Daniel R; Ocaña, Kary A C S; Ribeiro, Antonio C B; Emmel, Vanessa E; Probst, Christian M; Pitaluga, André N; Grisard, Edmundo C; Cavalcanti, Maria C; Campos, Maria L M; Mattoso, Marta; Dávila, Alberto M R

2014-03-07

The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/.

STINGRAY: system for integrated genomic resources and analysis

PubMed Central

2014-01-01

Background The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. Findings STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. Conclusion STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/. PMID:24606808

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression

PubMed Central

Libbrecht, Maxwell W.; Ay, Ferhat; Hoffman, Michael M.; Gilbert, David M.; Bilmes, Jeffrey A.; Noble, William Stafford

2015-01-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term “specific expression domains.” We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. PMID:25677182

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression.

PubMed

Libbrecht, Maxwell W; Ay, Ferhat; Hoffman, Michael M; Gilbert, David M; Bilmes, Jeffrey A; Noble, William Stafford

2015-04-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term "specific expression domains." We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. © 2015 Libbrecht et al.; Published by Cold Spring Harbor Laboratory Press.

Introduction to the fathead minnow genome browser and opportunities for collaborative development

EPA Science Inventory

Ab initio gene prediction and evidence alignment were used to produce the first annotations for the fathead minnow SOAPdenovo genome assembly. Additionally, a genome browser hosted at genome.setac.org provides simplified access to the annotation data in context with fathead minno...

Draft genome sequence of the marine bacterium Streptomyces griseoaurantiacus M045, which produces novel manumycin-type antibiotics with a pABA core component.

PubMed

Li, Fuchao; Jiang, Peng; Zheng, Huajun; Wang, Shengyue; Zhao, Guoping; Qin, Song; Liu, Zhaopu

2011-07-01

Streptomyces griseoaurantiacus M045, isolated from marine sediment, produces manumycin and chinikomycin antibiotics. Here we present a high-quality draft genome sequence of S. griseoaurantiacus M045, the first marine Streptomyces species to be sequenced and annotated. The genome encodes several gene clusters for biosynthesis of secondary metabolites and has provided insight into genomic islands linking secondary metabolism to functional adaptation in marine S. griseoaurantiacus M045.

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

DTIC Science & Technology

2012-11-15

the 28.7 Mb genome of N. oceanica CCMP1779. RNA sequencing data from nitrogen-replete and nitrogen- depleted growth conditions support a total of... sequence and its analysis, protocols for the transformation of N. oceanica CCMP1779 are provided. The availability of genomic and transcriptomic data for...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

Computational approaches to identify functional genetic variants in cancer genomes

PubMed Central

Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

2014-01-01

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana *

PubMed Central

Ndah, Elvis; Jonckheere, Veronique

2017-01-01

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes. PMID:28432195

N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana.

PubMed

Willems, Patrick; Ndah, Elvis; Jonckheere, Veronique; Stael, Simon; Sticker, Adriaan; Martens, Lennart; Van Breusegem, Frank; Gevaert, Kris; Van Damme, Petra

2017-06-01

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Genome sequencing and comparative genomics reveal a repertoire of putative pathogenicity genes in chilli anthracnose fungus Colletotrichum truncatum.

PubMed

Rao, Soumya; Nandineni, Madhusudan R

2017-01-01

Colletotrichum truncatum, a major fungal phytopathogen, causes the anthracnose disease on an economically important spice crop chilli (Capsicum annuum), resulting in huge economic losses in tropical and sub-tropical countries. It follows a subcuticular intramural infection strategy on chilli with a short, asymptomatic, endophytic phase, which contrasts with the intracellular hemibiotrophic lifestyle adopted by most of the Colletotrichum species. However, little is known about the molecular determinants and the mechanism of pathogenicity in this fungus. A high quality whole genome sequence and gene annotation based on transcriptome data of an Indian isolate of C. truncatum from chilli has been obtained. Analysis of the genome sequence revealed a rich repertoire of pathogenicity genes in C. truncatum encoding secreted proteins, effectors, plant cell wall degrading enzymes, secondary metabolism associated proteins, with potential roles in the host-specific infection strategy, placing it next only to the Fusarium species. The size of genome assembly, number of predicted genes and some of the functional categories were similar to other sequenced Colletotrichum species. The comparative genomic analyses with other species and related fungi identified some unique genes and certain highly expanded gene families of CAZymes, proteases and secondary metabolism associated genes in the genome of C. truncatum. The draft genome assembly and functional annotation of potential pathogenicity genes of C. truncatum provide an important genomic resource for understanding the biology and lifestyle of this important phytopathogen and will pave the way for designing efficient disease control regimens.

Genome sequencing and comparative genomics reveal a repertoire of putative pathogenicity genes in chilli anthracnose fungus Colletotrichum truncatum

PubMed Central

Rao, Soumya

2017-01-01

Colletotrichum truncatum, a major fungal phytopathogen, causes the anthracnose disease on an economically important spice crop chilli (Capsicum annuum), resulting in huge economic losses in tropical and sub-tropical countries. It follows a subcuticular intramural infection strategy on chilli with a short, asymptomatic, endophytic phase, which contrasts with the intracellular hemibiotrophic lifestyle adopted by most of the Colletotrichum species. However, little is known about the molecular determinants and the mechanism of pathogenicity in this fungus. A high quality whole genome sequence and gene annotation based on transcriptome data of an Indian isolate of C. truncatum from chilli has been obtained. Analysis of the genome sequence revealed a rich repertoire of pathogenicity genes in C. truncatum encoding secreted proteins, effectors, plant cell wall degrading enzymes, secondary metabolism associated proteins, with potential roles in the host-specific infection strategy, placing it next only to the Fusarium species. The size of genome assembly, number of predicted genes and some of the functional categories were similar to other sequenced Colletotrichum species. The comparative genomic analyses with other species and related fungi identified some unique genes and certain highly expanded gene families of CAZymes, proteases and secondary metabolism associated genes in the genome of C. truncatum. The draft genome assembly and functional annotation of potential pathogenicity genes of C. truncatum provide an important genomic resource for understanding the biology and lifestyle of this important phytopathogen and will pave the way for designing efficient disease control regimens. PMID:28846714

Complete nucleotide sequences and annotations of φ673 and φ674, two newly characterised lytic phages of Corynebacterium glutamicum ATCC 13032.

PubMed

Yomantas, Yurgis A V; Abalakina, Elena G; Lobanova, Juliya S; Mamontov, Victor A; Stoynova, Nataliya V; Mashko, Sergey V

2018-05-15

The genomes of two new lytic phages of Corynebacterium glutamicum ATCC 13032, φ673 and φ674, were sequenced and annotated (GenBank: MG324353, MG324354). Electron microscopy studies of both virions revealed that taxonomically they belong to the Siphoviridae family and have a polyhedral head with a width of 50 nm and a non-contractile tail with a length of 250 nm. The genomes of φ673 and φ674 consist of linear double-stranded DNA molecules with lengths of 44,530 bp (G+C = 51.1%) and 43,193 bp (G+C = 50.7%) and identical, protruding, cohesive 3' ends 13 nt in length. The level of identity between the φ673 and φ674 genomes is 85.2%. Two major structural proteins of each virion were separated via SDS-PAGE and identified using peptide mass fingerprinting. Based on bioinformatic analysis, 56 and 54 ORFs were predicted for φ673 and φ674, respectively. Only 20 of the putative gene products of φ673 and 20 of φ674 could be assigned to known functions. Both genomes were divided into functional modules. Nine putative promoters in the φ673 genome and eight in the φ674 genome were predicted. One bidirectional Rho-independent transcription terminator was identified and experimentally confirmed in each phage genome.

Draft genome of the leopard gecko, Eublepharis macularius.

PubMed

Xiong, Zijun; Li, Fang; Li, Qiye; Zhou, Long; Gamble, Tony; Zheng, Jiao; Kui, Ling; Li, Cai; Li, Shengbin; Yang, Huanming; Zhang, Guojie

2016-10-26

Geckos are among the most species-rich reptile groups and the sister clade to all other lizards and snakes. Geckos possess a suite of distinctive characteristics, including adhesive digits, nocturnal activity, hard, calcareous eggshells, and a lack of eyelids. However, one gecko clade, the Eublepharidae, appears to be the exception to most of these 'rules' and lacks adhesive toe pads, has eyelids, and lays eggs with soft, leathery eggshells. These differences make eublepharids an important component of any investigation into the underlying genomic innovations contributing to the distinctive phenotypes in 'typical' geckos. We report high-depth genome sequencing, assembly, and annotation for a male leopard gecko, Eublepharis macularius (Eublepharidae). Illumina sequence data were generated from seven insert libraries (ranging from 170 to 20 kb), representing a raw sequencing depth of 136X from 303 Gb of data, reduced to 84X and 187 Gb after filtering. The assembled genome of 2.02 Gb was close to the 2.23 Gb estimated by k-mer analysis. Scaffold and contig N50 sizes of 664 and 20 kb, respectively, were comparable to the previously published Gekko japonicus genome. Repetitive elements accounted for 42 % of the genome. Gene annotation yielded 24,755 protein-coding genes, of which 93 % were functionally annotated. CEGMA and BUSCO assessment showed that our assembly captured 91 % (225 of 248) of the core eukaryotic genes, and 76 % of vertebrate universal single-copy orthologs. Assembly of the leopard gecko genome provides a valuable resource for future comparative genomic studies of geckos and other squamate reptiles.

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

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.

Redefining the genetics of Murine Gammaherpesvirus 68 via transcriptome-based annotation

PubMed Central

Johnson, L. Steven; Willert, Erin K.; Virgin, Herbert W.

2010-01-01

Summary Viral genetic studies often focus on large open reading frames (ORFs) identified during genome annotation (ORF-based annotation). Here we provide a tool and software set for defining gene expression by murine gammaherpesvirus 68 (γHV68) nucleotide-by-nucleotide across the 119,450 basepair (bp) genome. These tools allowed us to determine that viral RNA expression was significantly more complex than predicted from ORF-based annotation, including over 73,000 nucleotides of unexpected transcription within 30 expressed genomic regions (EGRs). Approximately 90% of this RNA expression was antisense to genomic regions containing known large ORFs. We verified the existence of novel transcripts in three EGRs using standard methods to validate the approach and determined which parts of the transcriptome depend on protein or viral DNA synthesis. This redefines the genetic map of γHV68, indicates that herpesviruses contain significantly more genetic complexity than predicted from ORF-based genome annotations, and provides new tools and approaches for viral genetic studies. PMID:20542255

Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

PubMed

DePietro, Paul J; Julfayev, Elchin S; McLaughlin, William A

2013-10-21

Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources.

Quantification of the impact of PSI:Biology according to the annotations of the determined structures

PubMed Central

2013-01-01

Background Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. Results One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. Conclusions We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources. PMID:24139526

Separating the wheat from the chaff: systematic identification of functionally relevant noncoding variants in ADHD.

PubMed

Tong, J H S; Hawi, Z; Dark, C; Cummins, T D R; Johnson, B P; Newman, D P; Lau, R; Vance, A; Heussler, H S; Matthews, N; Bellgrove, M A; Pang, K C

2016-11-01

Attention deficit hyperactivity disorder (ADHD) is a highly heritable psychiatric condition with negative lifetime outcomes. Uncovering its genetic architecture should yield important insights into the neurobiology of ADHD and assist development of novel treatment strategies. Twenty years of candidate gene investigations and more recently genome-wide association studies have identified an array of potential association signals. In this context, separating the likely true from false associations ('the wheat' from 'the chaff') will be crucial for uncovering the functional biology of ADHD. Here, we defined a set of 2070 DNA variants that showed evidence of association with ADHD (or were in linkage disequilibrium). More than 97% of these variants were noncoding, and were prioritised for further exploration using two tools-genome-wide annotation of variants (GWAVA) and Combined Annotation-Dependent Depletion (CADD)-that were recently developed to rank variants based upon their likely pathogenicity. Capitalising on recent efforts such as the Encyclopaedia of DNA Elements and US National Institutes of Health Roadmap Epigenomics Projects to improve understanding of the noncoding genome, we subsequently identified 65 variants to which we assigned functional annotations, based upon their likely impact on alternative splicing, transcription factor binding and translational regulation. We propose that these 65 variants, which possess not only a high likelihood of pathogenicity but also readily testable functional hypotheses, represent a tractable shortlist for future experimental validation in ADHD. Taken together, this study brings into sharp focus the likely relevance of noncoding variants for the genetic risk associated with ADHD, and more broadly suggests a bioinformatics approach that should be relevant to other psychiatric disorders.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

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

USDA-ARS?s Scientific Manuscript database

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-...

Functional annotation of chemical libraries across diverse biological processes.

PubMed

Piotrowski, Jeff S; Li, Sheena C; Deshpande, Raamesh; Simpkins, Scott W; Nelson, Justin; Yashiroda, Yoko; Barber, Jacqueline M; Safizadeh, Hamid; Wilson, Erin; Okada, Hiroki; Gebre, Abraham A; Kubo, Karen; Torres, Nikko P; LeBlanc, Marissa A; Andrusiak, Kerry; Okamoto, Reika; Yoshimura, Mami; DeRango-Adem, Eva; van Leeuwen, Jolanda; Shirahige, Katsuhiko; Baryshnikova, Anastasia; Brown, Grant W; Hirano, Hiroyuki; Costanzo, Michael; Andrews, Brenda; Ohya, Yoshikazu; Osada, Hiroyuki; Yoshida, Minoru; Myers, Chad L; Boone, Charles

2017-09-01

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

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

PubMed

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

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Complete Genome Sequence of Listeria monocytogenes DFPST0073, Isolated from Imported Mexican Soft Cheese.

PubMed

Salazar, Joelle K; Gonsalves, Lauren J; Schill, Kristin M; Sanchez Leon, Maria; Anderson, Nathan; Keller, Susanne E

2018-06-07

The genome of Listeria monocytogenes strain DFPST0073, isolated from imported fresh Mexican soft cheese in 2003, was sequenced using the Illumina MiSeq platform. Reads were assembled using SPAdes, and genome annotation was performed using the NCBI Prokaryotic Genome Annotation Pipeline.

Homology to peptide pattern for annotation of carbohydrate-active enzymes and prediction of function.

PubMed

Busk, P K; Pilgaard, B; Lezyk, M J; Meyer, A S; Lange, L

2017-04-12

Carbohydrate-active enzymes are found in all organisms and participate in key biological processes. These enzymes are classified in 274 families in the CAZy database but the sequence diversity within each family makes it a major task to identify new family members and to provide basis for prediction of enzyme function. A fast and reliable method for de novo annotation of genes encoding carbohydrate-active enzymes is to identify conserved peptides in the curated enzyme families followed by matching of the conserved peptides to the sequence of interest as demonstrated for the glycosyl hydrolase and the lytic polysaccharide monooxygenase families. This approach not only assigns the enzymes to families but also provides functional prediction of the enzymes with high accuracy. We identified conserved peptides for all enzyme families in the CAZy database with Peptide Pattern Recognition. The conserved peptides were matched to protein sequence for de novo annotation and functional prediction of carbohydrate-active enzymes with the Hotpep method. Annotation of protein sequences from 12 bacterial and 16 fungal genomes to families with Hotpep had an accuracy of 0.84 (measured as F1-score) compared to semiautomatic annotation by the CAZy database whereas the dbCAN HMM-based method had an accuracy of 0.77 with optimized parameters. Furthermore, Hotpep provided a functional prediction with 86% accuracy for the annotated genes. Hotpep is available as a stand-alone application for MS Windows. Hotpep is a state-of-the-art method for automatic annotation and functional prediction of carbohydrate-active enzymes.

xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud[OPEN

PubMed Central

Merchant, Nirav

2016-01-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today’s pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant’s Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. PMID:27020957

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

PubMed

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

2016-04-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today's pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant's Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. © 2016 American Society of Plant Biologists. All rights reserved.

The draft genome of Corchorus olitorius cv. JRO-524 (Navin).

PubMed

Sarkar, Debabrata; Mahato, Ajay Kumar; Satya, Pratik; Kundu, Avijit; Singh, Sangeeta; Jayaswal, Pawan Kumar; Singh, Akshay; Bahadur, Kaushlendra; Pattnaik, Sasmita; Singh, Nisha; Chakraborty, Avrajit; Mandal, Nur Alam; Das, Debajeet; Basu, Tista; Sevanthi, Amitha Mithra; Saha, Dipnarayan; Datta, Subhojit; Kar, Chandan Sourav; Mitra, Jiban; Datta, Karabi; Karmakar, Pran Gobinda; Sharma, Tilak Raj; Mohapatra, Trilochan; Singh, Nagendra Kumar

2017-06-01

Here, we present the draft genome (377.3 Mbp) of Corchorus olitorious cv. JRO-524 (Navin), which is a leading dark jute variety developed from a cross between African (cv. Sudan Green) and indigenous (cv. JRO-632) types. We predicted from the draft genome a total of 57,087 protein-coding genes with annotated functions. We identified a large number of 1765 disease resistance-like and defense response genes in the jute genome. The annotated genes showed the highest sequence similarities with that of Theobroma cacao followed by Gossypium raimondii . Seven chromosome-scale genetically anchored pseudomolecules were constructed with a total size of 8.53 Mbp and used for synteny analyses with the cocoa and cotton genomes. Like other plant species, gypsy and copia retrotransposons were the most abundant classes of repeat elements in jute. The raw data of our study are available in SRA database of NCBI with accession number SRX1506532. The genome sequence has been deposited at DDBJ/EMBL/GenBank under the accession LLWS00000000, and the version described in this paper will be the first version (LLWS01000000).

Ensembl BioMarts: a hub for data retrieval across taxonomic space.

PubMed

Kinsella, Rhoda J; Kähäri, Andreas; Haider, Syed; Zamora, Jorge; Proctor, Glenn; Spudich, Giulietta; Almeida-King, Jeff; Staines, Daniel; Derwent, Paul; Kerhornou, Arnaud; Kersey, Paul; Flicek, Paul

2011-01-01

For a number of years the BioMart data warehousing system has proven to be a valuable resource for scientists seeking a fast and versatile means of accessing the growing volume of genomic data provided by the Ensembl project. The launch of the Ensembl Genomes project in 2009 complemented the Ensembl project by utilizing the same visualization, interactive and programming tools to provide users with a means for accessing genome data from a further five domains: protists, bacteria, metazoa, plants and fungi. The Ensembl and Ensembl Genomes BioMarts provide a point of access to the high-quality gene annotation, variation data, functional and regulatory annotation and evolutionary relationships from genomes spanning the taxonomic space. This article aims to give a comprehensive overview of the Ensembl and Ensembl Genomes BioMarts as well as some useful examples and a description of current data content and future objectives. Database URLs: http://www.ensembl.org/biomart/martview/; http://metazoa.ensembl.org/biomart/martview/; http://plants.ensembl.org/biomart/martview/; http://protists.ensembl.org/biomart/martview/; http://fungi.ensembl.org/biomart/martview/; http://bacteria.ensembl.org/biomart/martview/.

An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

PubMed Central

Jelokhani-Niaraki, Saber; Minuchehr, Zarrin; Nassiri, Mohammad Reza

2015-01-01

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data. PMID:25873847

An Ontology-Based GIS for Genomic Data Management of Rumen Microbes.

PubMed

Jelokhani-Niaraki, Saber; Tahmoorespur, Mojtaba; Minuchehr, Zarrin; Nassiri, Mohammad Reza

2015-03-01

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

Deep Investigation of Arabidopsis thaliana Junk DNA Reveals a Continuum between Repetitive Elements and Genomic Dark Matter

PubMed Central

Maumus, Florian; Quesneville, Hadi

2014-01-01

Eukaryotic genomes contain highly variable amounts of DNA with no apparent function. This so-called junk DNA is composed of two components: repeated and repeat-derived sequences (together referred to as the repeatome), and non-annotated sequences also known as genomic dark matter. Because of their high duplication rates as compared to other genomic features, transposable elements are predominant contributors to the repeatome and the products of their decay is thought to be a major source of genomic dark matter. Determining the origin and composition of junk DNA is thus important to help understanding genome evolution as well as host biology. In this study, we have used a combination of tools enabling to show that the repeatome from the small and reducing A. thaliana genome is significantly larger than previously thought. Furthermore, we present the concepts and results from a series of innovative approaches suggesting that a significant amount of the A. thaliana dark matter is of repetitive origin. As a tentative standard for the community, we propose a deep compendium annotation of the A. thaliana repeatome that may help addressing farther genome evolution as well as transcriptional and epigenetic regulation in this model plant. PMID:24709859

Using Markov chains of nucleotide sequences as a possible precursor to predict functional roles of human genome: a case study on inactive chromatin regions.

PubMed

Lee, K-E; Lee, E-J; Park, H-S

2016-08-30

Recent advances in computational epigenetics have provided new opportunities to evaluate n-gram probabilistic language models. In this paper, we describe a systematic genome-wide approach for predicting functional roles in inactive chromatin regions by using a sequence-based Markovian chromatin map of the human genome. We demonstrate that Markov chains of sequences can be used as a precursor to predict functional roles in heterochromatin regions and provide an example comparing two publicly available chromatin annotations of large-scale epigenomics projects: ENCODE project consortium and Roadmap Epigenomics consortium.

SNPnexus: assessing the functional relevance of genetic variation to facilitate the promise of precision medicine.

PubMed

Dayem Ullah, Abu Z; Oscanoa, Jorge; Wang, Jun; Nagano, Ai; Lemoine, Nicholas R; Chelala, Claude

2018-05-11

Broader functional annotation of genetic variation is a valuable means for prioritising phenotypically-important variants in further disease studies and large-scale genotyping projects. We developed SNPnexus to meet this need by assessing the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models. Since its previous release in 2012, we have made significant improvements to the annotation categories and updated the query and data viewing systems. The most notable changes include broader functional annotation of noncoding variants and expanding annotations to the most recent human genome assembly GRCh38/hg38. SNPnexus has now integrated rich resources from ENCODE and Roadmap Epigenomics Consortium to map and annotate the noncoding variants onto different classes of regulatory regions and noncoding RNAs as well as providing their predicted functional impact from eight popular non-coding variant scoring algorithms and computational methods. A novel functionality offered now is the support for neo-epitope predictions from leading tools to facilitate its use in immunotherapeutic applications. These updates to SNPnexus are in preparation for its future expansion towards a fully comprehensive computational workflow for disease-associated variant prioritization from sequencing data, placing its users at the forefront of translational research. SNPnexus is freely available at http://www.snp-nexus.org.

De novo-based transcriptome profiling of male-sterile and fertile watermelon lines

PubMed Central

Seo, Minseok; Jang, Yoon Jeong; Sim, Tae Yong; Cho, Seoae; Han, Sang-Wook

2017-01-01

The whole-genome sequence of watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai), a valuable horticultural crop worldwide, was released in 2013. Here, we compared a de novo-based approach (DBA) to a reference-based approach (RBA) using RNA-seq data, to aid in efforts to improve the annotation of the watermelon reference genome and to obtain biological insight into male-sterility in watermelon. We applied these techniques to available data from two watermelon lines: the male-sterile line DAH3615-MS and the male-fertile line DAH3615. Using DBA, we newly annotated 855 watermelon transcripts, and found gene functional clusters predicted to be related to stimulus responses, nucleic acid binding, transmembrane transport, homeostasis, and Golgi/vesicles. Among the DBA-annotated transcripts, 138 de novo-exclusive differentially-expressed genes (DEDEGs) related to male sterility were detected. Out of 33 randomly selected newly annotated transcripts and DEDEGs, 32 were validated by RT-qPCR. This study demonstrates the usefulness and reliability of the de novo transcriptome assembly in watermelon, and provides new insights for researchers exploring transcriptional blueprints with regard to the male sterility. PMID:29095876

Functional genomics of bio-energy plants and related patent activities.

PubMed

Jiang, Shu-Ye; Ramachandran, Srinivasan

2013-04-01

With dwindling fossil oil resources and increased economic growth of many developing countries due to globalization, energy driven from an alternative source such as bio-energy in a sustainable fashion is the need of the hour. However, production of energy from biological source is relatively expensive due to low starch and sugar contents of bioenergy plants leading to lower oil yield and reduced quality along with lower conversion efficiency of feedstock. In this context genetic improvement of bio-energy plants offers a viable solution. In this manuscript, we reviewed the current status of functional genomics studies and related patent activities in bio-energy plants. Currently, genomes of considerable bio-energy plants have been sequenced or are in progress and also large amount of expression sequence tags (EST) or cDNA sequences are available from them. These studies provide fundamental data for more reliable genome annotation and as a result, several genomes have been annotated in a genome-wide level. In addition to this effort, various mutagenesis tools have also been employed to develop mutant populations for characterization of genes that are involved in bioenergy quantitative traits. With the progress made on functional genomics of important bio-energy plants, more patents were filed with a significant number of them focusing on genes and DNA sequences which may involve in improvement of bio-energy traits including higher yield and quality of starch, sugar and oil. We also believe that these studies will lead to the generation of genetically altered plants with improved tolerance to various abiotic and biotic stresses.

Discovering novel subsystems using comparative genomics

PubMed Central

Ferrer, Luciana; Shearer, Alexander G.; Karp, Peter D.

2011-01-01

Motivation: Key problems for computational genomics include discovering novel pathways in genome data, and discovering functional interaction partners for genes to define new members of partially elucidated pathways. Results: We propose a novel method for the discovery of subsystems from annotated genomes. For each gene pair, a score measuring the likelihood that the two genes belong to a same subsystem is computed using genome context methods. Genes are then grouped based on these scores, and the resulting groups are filtered to keep only high-confidence groups. Since the method is based on genome context analysis, it relies solely on structural annotation of the genomes. The method can be used to discover new pathways, find missing genes from a known pathway, find new protein complexes or other kinds of functional groups and assign function to genes. We tested the accuracy of our method in Escherichia coli K-12. In one configuration of the system, we find that 31.6% of the candidate groups generated by our method match a known pathway or protein complex closely, and that we rediscover 31.2% of all known pathways and protein complexes of at least 4 genes. We believe that a significant proportion of the candidates that do not match any known group in E.coli K-12 corresponds to novel subsystems that may represent promising leads for future laboratory research. We discuss in-depth examples of these findings. Availability: Predicted subsystems are available at http://brg.ai.sri.com/pwy-discovery/journal.html. Contact: lferrer@ai.sri.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21775308

GFFview: A Web Server for Parsing and Visualizing Annotation Information of Eukaryotic Genome.

PubMed

Deng, Feilong; Chen, Shi-Yi; Wu, Zhou-Lin; Hu, Yongsong; Jia, Xianbo; Lai, Song-Jia

2017-10-01

Owing to wide application of RNA sequencing (RNA-seq) technology, more and more eukaryotic genomes have been extensively annotated, such as the gene structure, alternative splicing, and noncoding loci. Annotation information of genome is prevalently stored as plain text in General Feature Format (GFF), which could be hundreds or thousands Mb in size. Therefore, it is a challenge for manipulating GFF file for biologists who have no bioinformatic skill. In this study, we provide a web server (GFFview) for parsing the annotation information of eukaryotic genome and then generating statistical description of six indices for visualization. GFFview is very useful for investigating quality and difference of the de novo assembled transcriptome in RNA-seq studies.

Identification of functional candidates amongst hypothetical proteins of Treponema pallidum ssp. pallidum.

PubMed

Naqvi, Ahmad Abu Turab; Shahbaaz, Mohd; Ahmad, Faizan; Hassan, Md Imtaiyaz

2015-01-01

Syphilis is a globally occurring venereal disease, and its infection is propagated through sexual contact. The causative agent of syphilis, Treponema pallidum ssp. pallidum, a Gram-negative sphirochaete, is an obligate human parasite. Genome of T. pallidum ssp. pallidum SS14 strain (RefSeq NC_010741.1) encodes 1,027 proteins, of which 444 proteins are known as hypothetical proteins (HPs), i.e., proteins of unknown functions. Here, we performed functional annotation of HPs of T. pallidum ssp. pallidum using various database, domain architecture predictors, protein function annotators and clustering tools. We have analyzed the sequences of 444 HPs of T. pallidum ssp. pallidum and subsequently predicted the function of 207 HPs with a high level of confidence. However, functions of 237 HPs are predicted with less accuracy. We found various enzymes, transporters, binding proteins in the annotated group of HPs that may be possible molecular targets, facilitating for the survival of pathogen. Our comprehensive analysis helps to understand the mechanism of pathogenesis to provide many novel potential therapeutic interventions.

Swine transcriptome characterization by combined Iso-Seq and RNA-seq for annotating the emerging long read-based reference genome

USDA-ARS?s Scientific Manuscript database

PacBio long-read sequencing technology is increasingly popular in genome sequence assembly and transcriptome cataloguing. Recently, a new-generation pig reference genome was assembled based on long reads from this technology. To finely annotate this genome assembly, transcriptomes of nine tissues fr...

Sequencing, Annotation and Analysis of the Syrian Hamster (Mesocricetus auratus) Transcriptome

PubMed Central

Tchitchek, Nicolas; Safronetz, David; Rasmussen, Angela L.; Martens, Craig; Virtaneva, Kimmo; Porcella, Stephen F.; Feldmann, Heinz

2014-01-01

Background The Syrian hamster (golden hamster, Mesocricetus auratus) is gaining importance as a new experimental animal model for multiple pathogens, including emerging zoonotic diseases such as Ebola. Nevertheless there are currently no publicly available transcriptome reference sequences or genome for this species. Results A cDNA library derived from mRNA and snRNA isolated and pooled from the brains, lungs, spleens, kidneys, livers, and hearts of three adult female Syrian hamsters was sequenced. Sequence reads were assembled into 62,482 contigs and 111,796 reads remained unassembled (singletons). This combined contig/singleton dataset, designated as the Syrian hamster transcriptome, represents a total of 60,117,204 nucleotides. Our Mesocricetus auratus Syrian hamster transcriptome mapped to 11,648 mouse transcripts representing 9,562 distinct genes, and mapped to a similar number of transcripts and genes in the rat. We identified 214 quasi-complete transcripts based on mouse annotations. Canonical pathways involved in a broad spectrum of fundamental biological processes were significantly represented in the library. The Syrian hamster transcriptome was aligned to the current release of the Chinese hamster ovary (CHO) cell transcriptome and genome to improve the genomic annotation of this species. Finally, our Syrian hamster transcriptome was aligned against 14 other rodents, primate and laurasiatheria species to gain insights about the genetic relatedness and placement of this species. Conclusions This Syrian hamster transcriptome dataset significantly improves our knowledge of the Syrian hamster's transcriptome, especially towards its future use in infectious disease research. Moreover, this library is an important resource for the wider scientific community to help improve genome annotation of the Syrian hamster and other closely related species. Furthermore, these data provide the basis for development of expression microarrays that can be used in functional genomics studies. PMID:25398096

The Genome Sequence of Mannheimia haemolytica A1: Insights into Virulence, Natural Competence, and Pasteurellaceae Phylogeny†

PubMed Central

Gioia, Jason; Qin, Xiang; Jiang, Huaiyang; Clinkenbeard, Kenneth; Lo, Reggie; Liu, Yamei; Fox, George E.; Yerrapragada, Shailaja; McLeod, Michael P.; McNeill, Thomas Z.; Hemphill, Lisa; Sodergren, Erica; Wang, Qiaoyan; Muzny, Donna M.; Homsi, Farah J.; Weinstock, George M.; Highlander, Sarah K.

2006-01-01

The draft genome sequence of Mannheimia haemolytica A1, the causative agent of bovine respiratory disease complex (BRDC), is presented. Strain ATCC BAA-410, isolated from the lung of a calf with BRDC, was the DNA source. The annotated genome includes 2,839 coding sequences, 1,966 of which were assigned a function and 436 of which are unique to M. haemolytica. Through genome annotation many features of interest were identified, including bacteriophages and genes related to virulence, natural competence, and transcriptional regulation. In addition to previously described virulence factors, M. haemolytica encodes adhesins, including the filamentous hemagglutinin FhaB and two trimeric autotransporter adhesins. Two dual-function immunoglobulin-protease/adhesins are also present, as is a third immunoglobulin protease. Genes related to iron acquisition and drug resistance were identified and are likely important for survival in the host and virulence. Analysis of the genome indicates that M. haemolytica is naturally competent, as genes for natural competence and DNA uptake signal sequences (USS) are present. Comparison of competence loci and USS in other species in the family Pasteurellaceae indicates that M. haemolytica, Actinobacillus pleuropneumoniae, and Haemophilus ducreyi form a lineage distinct from other Pasteurellaceae. This observation was supported by a phylogenetic analysis using sequences of predicted housekeeping genes. PMID:17015664

GenoQuery: a new querying module for functional annotation in a genomic warehouse

PubMed Central

Lemoine, Frédéric; Labedan, Bernard; Froidevaux, Christine

2008-01-01

Motivation: We have to cope with both a deluge of new genome sequences and a huge amount of data produced by high-throughput approaches used to exploit these genomic features. Crossing and comparing such heterogeneous and disparate data will help improving functional annotation of genomes. This requires designing elaborate integration systems such as warehouses for storing and querying these data. Results: We have designed a relational genomic warehouse with an original multi-layer architecture made of a databases layer and an entities layer. We describe a new querying module, GenoQuery, which is based on this architecture. We use the entities layer to define mixed queries. These mixed queries allow searching for instances of biological entities and their properties in the different databases, without specifying in which database they should be found. Accordingly, we further introduce the central notion of alternative queries. Such queries have the same meaning as the original mixed queries, while exploiting complementarities yielded by the various integrated databases of the warehouse. We explain how GenoQuery computes all the alternative queries of a given mixed query. We illustrate how useful this querying module is by means of a thorough example. Availability: http://www.lri.fr/~lemoine/GenoQuery/ Contact: chris@lri.fr, lemoine@lri.fr PMID:18586731

GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data

PubMed Central

Jung, Sook; Staton, Margaret; Lee, Taein; Blenda, Anna; Svancara, Randall; Abbott, Albert; Main, Dorrie

2008-01-01

The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org. PMID:17932055

MIPS: curated databases and comprehensive secondary data resources in 2010.

PubMed

Mewes, H Werner; Ruepp, Andreas; Theis, Fabian; Rattei, Thomas; Walter, Mathias; Frishman, Dmitrij; Suhre, Karsten; Spannagl, Manuel; Mayer, Klaus F X; Stümpflen, Volker; Antonov, Alexey

2011-01-01

The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38,000,000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de).

MIPS: curated databases and comprehensive secondary data resources in 2010

PubMed Central

Mewes, H. Werner; Ruepp, Andreas; Theis, Fabian; Rattei, Thomas; Walter, Mathias; Frishman, Dmitrij; Suhre, Karsten; Spannagl, Manuel; Mayer, Klaus F.X.; Stümpflen, Volker; Antonov, Alexey

2011-01-01

The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38 000 000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de). PMID:21109531

MIPS: analysis and annotation of genome information in 2007

PubMed Central

Mewes, H. W.; Dietmann, S.; Frishman, D.; Gregory, R.; Mannhaupt, G.; Mayer, K. F. X.; Münsterkötter, M.; Ruepp, A.; Spannagl, M.; Stümpflen, V.; Rattei, T.

2008-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:18158298

MIPS: analysis and annotation of genome information in 2007.

PubMed

Mewes, H W; Dietmann, S; Frishman, D; Gregory, R; Mannhaupt, G; Mayer, K F X; Münsterkötter, M; Ruepp, A; Spannagl, M; Stümpflen, V; Rattei, T

2008-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

P2RP: a Web-based framework for the identification and analysis of regulatory proteins in prokaryotic genomes.

PubMed

Barakat, Mohamed; Ortet, Philippe; Whitworth, David E

2013-04-20

Regulatory proteins (RPs) such as transcription factors (TFs) and two-component system (TCS) proteins control how prokaryotic cells respond to changes in their external and/or internal state. Identification and annotation of TFs and TCSs is non-trivial, and between-genome comparisons are often confounded by different standards in annotation. There is a need for user-friendly, fast and convenient tools to allow researchers to overcome the inherent variability in annotation between genome sequences. We have developed the web-server P2RP (Predicted Prokaryotic Regulatory Proteins), which enables users to identify and annotate TFs and TCS proteins within their sequences of interest. Users can input amino acid or genomic DNA sequences, and predicted proteins therein are scanned for the possession of DNA-binding domains and/or TCS domains. RPs identified in this manner are categorised into families, unambiguously annotated, and a detailed description of their features generated, using an integrated software pipeline. P2RP results can then be outputted in user-specified formats. Biologists have an increasing need for fast and intuitively usable tools, which is why P2RP has been developed as an interactive system. As well as assisting experimental biologists to interrogate novel sequence data, it is hoped that P2RP will be built into genome annotation pipelines and re-annotation processes, to increase the consistency of RP annotation in public genomic sequences. P2RP is the first publicly available tool for predicting and analysing RP proteins in users' sequences. The server is freely available and can be accessed along with documentation at http://www.p2rp.org.

The history of the CATH structural classification of protein domains.

PubMed

Sillitoe, Ian; Dawson, Natalie; Thornton, Janet; Orengo, Christine

2015-12-01

This article presents a historical review of the protein structure classification database CATH. Together with the SCOP database, CATH remains comprehensive and reasonably up-to-date with the now more than 100,000 protein structures in the PDB. We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains. The establishment of comprehensive function annotation resources has also meant that domain families can be functionally annotated allowing insights into functional divergence and evolution within protein families. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

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. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Assembly and comparison of two closely related Brassica napus genomes.

PubMed

Bayer, Philipp E; Hurgobin, Bhavna; Golicz, Agnieszka A; Chan, Chon-Kit Kenneth; Yuan, Yuxuan; Lee, HueyTyng; Renton, Michael; Meng, Jinling; Li, Ruiyuan; Long, Yan; Zou, Jun; Bancroft, Ian; Chalhoub, Boulos; King, Graham J; Batley, Jacqueline; Edwards, David

2017-12-01

As an increasing number of plant genome sequences become available, it is clear that gene content varies between individuals, and the challenge arises to predict the gene content of a species. However, genome comparison is often confounded by variation in assembly and annotation. Differentiating between true gene absence and variation in assembly or annotation is essential for the accurate identification of conserved and variable genes in a species. Here, we present the de novo assembly of the B. napus cultivar Tapidor and comparison with an improved assembly of the Brassica napus cultivar Darmor-bzh. Both cultivars were annotated using the same method to allow comparison of gene content. We identified genes unique to each cultivar and differentiate these from artefacts due to variation in the assembly and annotation. We demonstrate that using a common annotation pipeline can result in different gene predictions, even for closely related cultivars, and repeat regions which collapse during assembly impact whole genome comparison. After accounting for differences in assembly and annotation, we demonstrate that the genome of Darmor-bzh contains a greater number of genes than the genome of Tapidor. Our results are the first step towards comparison of the true differences between B. napus genomes and highlight the potential sources of error in future production of a B. napus pangenome. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

AGeNNT: annotation of enzyme families by means of refined neighborhood networks.

PubMed

Kandlinger, Florian; Plach, Maximilian G; Merkl, Rainer

2017-05-25

Large enzyme families may contain functionally diverse members that give rise to clusters in a sequence similarity network (SSN). In prokaryotes, the genome neighborhood of a gene-product is indicative of its function and thus, a genome neighborhood network (GNN) deduced for an SSN provides strong clues to the specific function of enzymes constituting the different clusters. The Enzyme Function Initiative ( http://enzymefunction.org/ ) offers services that compute SSNs and GNNs. We have implemented AGeNNT that utilizes these services, albeit with datasets purged with respect to unspecific protein functions and overrepresented species. AGeNNT generates refined GNNs (rGNNs) that consist of cluster-nodes representing the sequences under study and Pfam-nodes representing enzyme functions encoded in the respective neighborhoods. For cluster-nodes, AGeNNT summarizes the phylogenetic relationships of the contributing species and a statistic indicates how unique nodes and GNs are within this rGNN. Pfam-nodes are annotated with additional features like GO terms describing protein function. For edges, the coverage is given, which is the relative number of neighborhoods containing the considered enzyme function (Pfam-node). AGeNNT is available at https://github.com/kandlinf/agennt . An rGNN is easier to interpret than a conventional GNN, which commonly contains proteins without enzymatic function and overly specific neighborhoods due to phylogenetic bias. The implemented filter routines and the statistic allow the user to identify those neighborhoods that are most indicative of a specific metabolic capacity. Thus, AGeNNT facilitates to distinguish and annotate functionally different members of enzyme families.

Genome Annotation and Transcriptomics of Oil-Producing Algae

DTIC Science & Technology

2015-03-16

AFRL-OSR-VA-TR-2015-0103 GENOME ANNOTATION AND TRANSCRIPTOMICS OF OIL-PRODUCING ALGAE Sabeeha Merchant UNIVERSITY OF CALIFORNIA LOS ANGELES Final...2010 To 12-31-2014 4. TITLE AND SUBTITLE GENOME ANNOTATION AND TRANSCRIPTOMICS OF OIL-PRODUCING ALGAE 5a. CONTRACT NUMBER FA9550-10-1-0095 5b...NOTES 14. ABSTRACT Most algae accumulate triacylglycerols (TAGs) when they are starved for essential nutrients like N, S, P (or Si in the case of some

Decoding the similarities and differences among mycobacterial species

PubMed Central

Vedithi, Sundeep Chaitanya; Blundell, Tom L.

2017-01-01

Mycobacteriaceae comprises pathogenic species such as Mycobacterium tuberculosis, M. leprae and M. abscessus, as well as non-pathogenic species, for example, M. smegmatis and M. thermoresistibile. Genome comparison and annotation studies provide insights into genome evolutionary relatedness, identify unique and pathogenicity-related genes in each species, and explore new targets that could be used for developing new diagnostics and therapeutics. Here, we present a comparative analysis of ten-mycobacterial genomes with the objective of identifying similarities and differences between pathogenic and non-pathogenic species. We identified 1080 core orthologous clusters that were enriched in proteins involved in amino acid and purine/pyrimidine biosynthetic pathways, DNA-related processes (replication, transcription, recombination and repair), RNA-methylation and modification, and cell-wall polysaccharide biosynthetic pathways. For their pathogenicity and survival in the host cell, pathogenic species have gained specific sets of genes involved in repair and protection of their genomic DNA. M. leprae is of special interest owing to its smallest genome (1600 genes and ~1300 psuedogenes), yet poor genome annotation. More than 75% of the pseudogenes were found to have a functional ortholog in the other mycobacterial genomes and belong to protein families such as transferases, oxidoreductases and hydrolases. PMID:28854187

[Complete genome sequencing of polymalic acid-producing strain Aureobasidium pullulans CCTCC M2012223].

PubMed

Wang, Yongkang; Song, Xiaodan; Li, Xiaorong; Yang, Sang-tian; Zou, Xiang

2017-01-04

To explore the genome sequence of Aureobasidium pullulans CCTCC M2012223, analyze the key genes related to the biosynthesis of important metabolites, and provide genetic background for metabolic engineering. Complete genome of A. pullulans CCTCC M2012223 was sequenced by Illumina HiSeq high throughput sequencing platform. Then, fragment assembly, gene prediction, functional annotation, and GO/COG cluster were analyzed in comparison with those of other five A. pullulans varieties. The complete genome sequence of A. pullulans CCTCC M2012223 was 30756831 bp with an average GC content of 47.49%, and 9452 genes were successfully predicted. Genome-wide analysis showed that A. pullulans CCTCC M2012223 had the biggest genome assembly size. Protein sequences involved in the pullulan and polymalic acid pathway were highly conservative in all of six A. pullulans varieties. Although both A. pullulans CCTCC M2012223 and A. pullulans var. melanogenum have a close affinity, some point mutation and inserts were occurred in protein sequences involved in melanin biosynthesis. Genome information of A. pullulans CCTCC M2012223 was annotated and genes involved in melanin, pullulan and polymalic acid pathway were compared, which would provide a theoretical basis for genetic modification of metabolic pathway in A. pullulans.

De novo RNA-seq and functional annotation of Ornithonyssus bacoti.

PubMed

Niu, DongLing; Wang, RuiLing; Zhao, YaE; Yang, Rui; Hu, Li

2018-06-01

Ornithonyssus bacoti (Hirst) (Acari: Macronyssidae) is a vector and reservoir of pathogens causing serious infectious diseases, such as epidemic hemorrhagic fever, endemic typhus, tularemia, and leptospirosis. Its genome and transcriptome data are lacking in public databases. In this study, total RNA was extracted from live O. bacoti to conduct RNA-seq, functional annotation, coding domain sequence (CDS) prediction and simple sequence repeats (SSRs) detection. The results showed that 65.8 million clean reads were generated and assembled into 72,185 unigenes, of which 49.4% were annotated by seven functional databases. 23,121 unigenes were annotated and assigned to 457 species by non-redundant protein sequence database. The BLAST top-two hit species were Metaseiulus occidentalis and Ixodes scapularis. The procedure detected 12,426 SSRs, of which tri- and di-nucleotides were the most abundant types and the representative motifs were AAT/ATT and AC/GT. 26,936 CDS were predicted with a mean length of 711 bp. 87 unigenes of 30 functional genes, which are usually involved in stress responses, drug resistance, movement, metabolism and allergy, were further identified by bioinformatics methods. The unigenes putatively encoding cytochrome P450 proteins were further analyzed phylogenetically. In conclusion, this study completed the RNA-seq and functional annotation of O. bacoti successfully, which provides reliable molecular data for its future studies of gene function and molecular markers.

i5k | National Agricultural Library

Science.gov Websites

genome browser, and the Apollo manual curation service. Over 50 arthropod genomes are now part of the i5k (done by Dan Hughes at Baylor) with manual annotations by the research community (done via Web Apollo with manual annotations by the research community (via the Apollo manual annotation software). insects

The COG database: a tool for genome-scale analysis of protein functions and evolution

PubMed Central

Tatusov, Roman L.; Galperin, Michael Y.; Natale, Darren A.; Koonin, Eugene V.

2000-01-01

Rational classification of proteins encoded in sequenced genomes is critical for making the genome sequences maximally useful for functional and evolutionary studies. The database of Clusters of Orthologous Groups of proteins (COGs) is an attempt on a phylogenetic classification of the proteins encoded in 21 complete genomes of bacteria, archaea and eukaryotes (http://www.ncbi.nlm.nih.gov/COG ). The COGs were constructed by applying the criterion of consistency of genome-specific best hits to the results of an exhaustive comparison of all protein sequences from these genomes. The database comprises 2091 COGs that include 56–83% of the gene products from each of the complete bacterial and archaeal genomes and ~35% of those from the yeast Saccharomyces cerevisiae genome. The COG database is accompanied by the COGNITOR program that is used to fit new proteins into the COGs and can be applied to functional and phylogenetic annotation of newly sequenced genomes. PMID:10592175

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

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

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

PubMed

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

2014-06-12

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

PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes.

PubMed

Bhawna; Bonthala, V S; Gajula, Mnv Prasad

2016-01-01

The common bean [Phaseolus vulgaris (L.)] is one of the essential proteinaceous vegetables grown in developing countries. However, its production is challenged by low yields caused by numerous biotic and abiotic stress conditions. Regulatory transcription factors (TFs) symbolize a key component of the genome and are the most significant targets for producing stress tolerant crop and hence functional genomic studies of these TFs are important. Therefore, here we have constructed a web-accessible TFs database for P. vulgaris, called PvTFDB, which contains 2370 putative TF gene models in 49 TF families. This database provides a comprehensive information for each of the identified TF that includes sequence data, functional annotation, SSRs with their primer sets, protein physical properties, chromosomal location, phylogeny, tissue-specific gene expression data, orthologues, cis-regulatory elements and gene ontology (GO) assignment. Altogether, this information would be used in expediting the functional genomic studies of a specific TF(s) of interest. The objectives of this database are to understand functional genomics study of common bean TFs and recognize the regulatory mechanisms underlying various stress responses to ease breeding strategy for variety production through a couple of search interfaces including gene ID, functional annotation and browsing interfaces including by family and by chromosome. This database will also serve as a promising central repository for researchers as well as breeders who are working towards crop improvement of legume crops. In addition, this database provide the user unrestricted public access and the user can download entire data present in the database freely.Database URL: http://www.multiomics.in/PvTFDB/. © The Author(s) 2016. Published by Oxford University Press.

CycADS: an annotation database system to ease the development and update of BioCyc databases

PubMed Central

Vellozo, Augusto F.; Véron, Amélie S.; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E.; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano

2011-01-01

In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org PMID:21474551

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

PubMed

Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .

Using hidden Markov models and observed evolution to annotate viral genomes.

PubMed

McCauley, Stephen; Hein, Jotun

2006-06-01

ssRNA (single stranded) viral genomes are generally constrained in length and utilize overlapping reading frames to maximally exploit the coding potential within the genome length restrictions. This overlapping coding phenomenon leads to complex evolutionary constraints operating on the genome. In regions which code for more than one protein, silent mutations in one reading frame generally have a protein coding effect in another. To maximize coding flexibility in all reading frames, overlapping regions are often compositionally biased towards amino acids which are 6-fold degenerate with respect to the 64 codon alphabet. Previous methodologies have used this fact in an ad hoc manner to look for overlapping genes by motif matching. In this paper differentiated nucleotide compositional patterns in overlapping regions are incorporated into a probabilistic hidden Markov model (HMM) framework which is used to annotate ssRNA viral genomes. This work focuses on single sequence annotation and applies an HMM framework to ssRNA viral annotation. A description of how the HMM is parameterized, whilst annotating within a missing data framework is given. A Phylogenetic HMM (Phylo-HMM) extension, as applied to 14 aligned HIV2 sequences is also presented. This evolutionary extension serves as an illustration of the potential of the Phylo-HMM framework for ssRNA viral genomic annotation. The single sequence annotation procedure (SSA) is applied to 14 different strains of the HIV2 virus. Further results on alternative ssRNA viral genomes are presented to illustrate more generally the performance of the method. The results of the SSA method are encouraging however there is still room for improvement, and since there is overwhelming evidence to indicate that comparative methods can improve coding sequence (CDS) annotation, the SSA method is extended to a Phylo-HMM to incorporate evolutionary information. The Phylo-HMM extension is applied to the same set of 14 HIV2 sequences which are pre-aligned. The performance improvement that results from including the evolutionary information in the analysis is illustrated.

PATtyFams: Protein families for the microbial genomes in the PATRIC database

DOE PAGES

Davis, James J.; Gerdes, Svetlana; Olsen, Gary J.; ...

2016-02-08

The ability to build accurate protein families is a fundamental operation in bioinformatics that influences comparative analyses, genome annotation, and metabolic modeling. For several years we have been maintaining protein families for all microbial genomes in the PATRIC database (Pathosystems Resource Integration Center, patricbrc.org) in order to drive many of the comparative analysis tools that are available through the PATRIC website. However, due to the burgeoning number of genomes, traditional approaches for generating protein families are becoming prohibitive. In this report, we describe a new approach for generating protein families, which we call PATtyFams. This method uses the k-mer-based functionmore » assignments available through RAST (Rapid Annotation using Subsystem Technology) to rapidly guide family formation, and then differentiates the function-based groups into families using a Markov Cluster algorithm (MCL). In conclusion, this new approach for generating protein families is rapid, scalable and has properties that are consistent with alignment-based methods.« less

The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization

PubMed Central

Nelson, David R; Khraiwesh, Basel; Fu, Weiqi; Alseekh, Saleh; Jaiswal, Ashish; Chaiboonchoe, Amphun; Hazzouri, Khaled M; O’Connor, Matthew J; Butterfoss, Glenn L; Drou, Nizar; Rowe, Jillian D; Harb, Jamil; Fernie, Alisdair R; Gunsalus, Kristin C; Salehi-Ashtiani, Kourosh

2017-01-01

To investigate the phenomic and genomic traits that allow green algae to survive in deserts, we characterized a ubiquitous species, Chloroidium sp. UTEX 3007, which we isolated from multiple locations in the United Arab Emirates (UAE). Metabolomic analyses of Chloroidium sp. UTEX 3007 indicated that the alga accumulates a broad range of carbon sources, including several desiccation tolerance-promoting sugars and unusually large stores of palmitate. Growth assays revealed capacities to grow in salinities from zero to 60 g/L and to grow heterotrophically on >40 distinct carbon sources. Assembly and annotation of genomic reads yielded a 52.5 Mbp genome with 8153 functionally annotated genes. Comparison with other sequenced green algae revealed unique protein families involved in osmotic stress tolerance and saccharide metabolism that support phenomic studies. Our results reveal the robust and flexible biology utilized by a green alga to successfully inhabit a desert coastline. DOI: http://dx.doi.org/10.7554/eLife.25783.001 PMID:28623667

PATtyFams: Protein families for the microbial genomes in the PATRIC database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, James J.; Gerdes, Svetlana; Olsen, Gary J.

The ability to build accurate protein families is a fundamental operation in bioinformatics that influences comparative analyses, genome annotation, and metabolic modeling. For several years we have been maintaining protein families for all microbial genomes in the PATRIC database (Pathosystems Resource Integration Center, patricbrc.org) in order to drive many of the comparative analysis tools that are available through the PATRIC website. However, due to the burgeoning number of genomes, traditional approaches for generating protein families are becoming prohibitive. In this report, we describe a new approach for generating protein families, which we call PATtyFams. This method uses the k-mer-based functionmore » assignments available through RAST (Rapid Annotation using Subsystem Technology) to rapidly guide family formation, and then differentiates the function-based groups into families using a Markov Cluster algorithm (MCL). In conclusion, this new approach for generating protein families is rapid, scalable and has properties that are consistent with alignment-based methods.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Richard A.; Brown, Joseph M.; Colby, Sean M.

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

AnnoTALE: bioinformatics tools for identification, annotation, and nomenclature of TALEs from Xanthomonas genomic sequences

PubMed Central

Grau, Jan; Reschke, Maik; Erkes, Annett; Streubel, Jana; Morgan, Richard D.; Wilson, Geoffrey G.; Koebnik, Ralf; Boch, Jens

2016-01-01

Transcription activator-like effectors (TALEs) are virulence factors, produced by the bacterial plant-pathogen Xanthomonas, that function as gene activators inside plant cells. Although the contribution of individual TALEs to infectivity has been shown, the specific roles of most TALEs, and the overall TALE diversity in Xanthomonas spp. is not known. TALEs possess a highly repetitive DNA-binding domain, which is notoriously difficult to sequence. Here, we describe an improved method for characterizing TALE genes by the use of PacBio sequencing. We present ‘AnnoTALE’, a suite of applications for the analysis and annotation of TALE genes from Xanthomonas genomes, and for grouping similar TALEs into classes. Based on these classes, we propose a unified nomenclature for Xanthomonas TALEs that reveals similarities pointing to related functionalities. This new classification enables us to compare related TALEs and to identify base substitutions responsible for the evolution of TALE specificities. PMID:26876161

The Schistosoma mansoni phylome: using evolutionary genomics to gain insight into a parasite's biology.

PubMed

Silva, Larissa Lopes; Marcet-Houben, Marina; Nahum, Laila Alves; Zerlotini, Adhemar; Gabaldón, Toni; Oliveira, Guilherme

2012-11-13

Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni's proteome evolution and to improve its functional annotation. Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org). In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite's biology as well as host-parasite interactions.

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

PubMed

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

2016-10-04

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. Copyright © 2016 Baric et al.